autotrust/JEV-27B

hf autotrust/JEV-27B 2 sources, 2 claims · Watch

What each source says

PropertySourceSaidMeans here
Author
author
not compared
GGUF quantisationsprithivMLmods
receipt
Source
GGUF quantisations
Its words
prithivMLmods
Read by
field:author
Said since
2026-09-28 11:46 UTC
Last answered
2026-10-02 18:04 UTC
Original
open at the source
What the source handed over
{
  "_id": "6ab9ec46eaeed75d3ad4d76f",
  "author": "prithivMLmods",
  "cardData": {
    "base_model": [
      "autotrust/JEV-27B"
    ],
    "datasets": [
      "SargeDev/jev-distill-corpus-v3"
    ],
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "pipeline_tag": "text-classification",
    "tags": [
      "text-generation-inference",
      "llama-cpp",
      "system-one",
      "system-two",
      "blocks-of-experts",
      "typed-decisions",
      "decision-model",
      "calibrated-probabilities",
      "knowledge-distillation",
      "jev",
      "noul",
      "choice",
      "score",
      "qwen3_5",
      "qwen3_5_text",
      "text-generation",
      "dual-head"
    ]
  },
  "createdAt": "2026-09-28T04:25:42.000Z",
  "downloads": 796,
  "gated": false,
  "id": "prithivMLmods/JEV-27B-GGUF",
  "lastModified": "2026-09-28T04:43:44.000Z",
  "library_name": "transformers",
  "likes": 2,
  "modelId": "prithivMLmods/JEV-27B-GGUF",
  "pipeline_tag": "text-classification",
  "private": false,
  "sha": "626d9cc86def467b9ae666c6ed631e8d9f06fd10",
  "siblings": [
    {
      "rfilename": ".gitattributes"
    },
    {
      "rfilename": "JEV-27B.BF16.gguf"
    },
    {
      "rfilename": "JEV-27B.Q3_K_M.gguf"
    },
    {
      "rfilename": "JEV-27B.Q4_K_M.gguf"
    },
    {
      "rfilename": "JEV-27B.Q5_K_M.gguf"
    },
    {
      "rfilename": "README.md"
    }
  ],
  "tags": [
    "transformers",
    "gguf",
    "text-generation-inference",
    "llama-cpp",
    "system-one",
    "system-two",
    "blocks-of-experts",
    "typed-decisions",
    "decision-model",
    "calibrated-probabilities",
    "knowledge-distillation",
    "jev",
    "noul",
    "choice",
    "score",
    "qwen3_5",
    "qwen3_5_text",
    "text-generation",
    "dual-head",
    "text-classification",
    "en",
    "dataset:SargeDev/jev-distill-corpus-v3",
    "base_model:autotrust/JEV-27B",
    "base_model:quantized:autotrust/JEV-27B",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ]
}
—
Author
author
not compared
Hugging Face modelsautotrust
receipt
Source
Hugging Face models
Its words
autotrust
Read by
field:author
Said since
2026-10-02 12:02 UTC
Original
open at the source
What the source handed over
{
  "_asked": "autotrust/JEV-27B",
  "_id": "6ab66ffdf7bd8732d74b7264",
  "author": "autotrust",
  "cardData": {
    "base_model": "Qwen/Qwen3.8-27B",
    "base_model_relation": "finetune",
    "datasets": [
      "SargeDev/jev-distill-corpus-v3"
    ],
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "metrics": [
      "kl",
      "auroc",
      "brier",
      "ece"
    ],
    "model-index": [
      {
        "name": "autotrust/JEV-27B (student of TypeSafe Jev 1.13)",
        "results": [
          {
            "dataset": {
              "name": "jev-distill-corpus-v3 · test_set_30k",
              "split": "test_set_30k",
              "type": "SargeDev/jev-distill-corpus-v3"
            },
            "metrics": [
              {
                "name": "mean KL(target ‖ model), all test rows (25,376 of 29,955 targets are TypeSafe Jev 1.13 distributions)",
                "type": "kl_divergence",
                "value": 0.0186,
                "verified": false
              },
              {
                "name": "noul AUROC",
                "type": "auroc",
                "value": 0.996,
                "verified": false
              },
              {
                "name": "noul Brier (vs. target probability, all rows)",
                "type": "brier",
                "value": 0.0013,
                "verified": false
              },
              {
                "name": "score expected-value MAE (0–5 scale)",
                "type": "mae",
                "value": 0.098,
                "verified": false
              },
              {
                "name": "ECE (15 bins, after temperature)",
                "type": "ece",
                "value": 0.0009,
                "verified": false
              },
              {
                "name": "choice top-1 agreement (all rows)",
                "type": "accuracy",
                "value": 0.903,
                "verified": false
              },
              {
                "name": "choice top-1 agreement (decisive-target rows, top-2 gap ≥ 0.1)",
                "type": "accuracy",
                "value": 0.958,
                "verified": false
              }
            ],
            "task": {
              "name": "typed decisions (noul / choice / score) — agreement with the TypeSafe Jev 1.13 teacher",
              "type": "text-classification"
            }
          },
          {
            "dataset": {
              "name": "HumanEval",
              "split": "test",
              "type": "openai/openai_humaneval"
            },
            "metrics": [
              {
                "name": "pass@1 (greedy, completion-style prompt)",
                "type": "pass@1",
                "value": 0.78,
                "verified": false
              }
            ],
            "task": {
              "name": "code generation — System 2 path (base lm_head, adapter off)",
              "type": "text-generation"
            }
          }
        ]
      }
    ],
    "pipeline_tag": "text-classification",
    "tags": [
      "system-one",
      "system-two",
      "blocks-of-experts",
      "typed-decisions",
      "decision-model",
      "calibrated-probabilities",
      "knowledge-distillation",
      "jev",
      "noul",
      "choice",
      "score",
      "lora",
      "qwen3_5",
      "text-generation",
      "dual-head",
      "vllm"
    ]
  },
  "config": {
    "architectures": [
      "Qwen3_5ForCausalLM"
    ],
    "chat_template_jinja": "{%- set image_count = namespace(value=0) %}\n{%- set video_count = namespace(value=0) %}\n{%- macro render_content(content, do_vision_count, is_system_content=false) %}\n    {%- if content is string %}\n        {{- content }}\n    {%- elif content is iterable and content is not mapping %}\n        {%- for item in content %}\n            {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}\n                {%- if is_system_content %}\n                    {{- raise_exception('System message cannot contain images.') }}\n                {%- endif %}\n                {%- if do_vision_count %}\n                    {%- set image_count.value = image_count.value + 1 %}\n                {%- endif %}\n                {%- if add_vision_id %}\n                    {{- 'Picture ' ~ image_count.value ~ ': ' }}\n                {%- endif %}\n                {{- '<|vision_start|><|image_pad|><|vision_end|>' }}\n            {%- elif 'video' in item or item.type == 'video' %}\n                {%- if is_system_content %}\n                    {{- raise_exception('System message cannot contain videos.') }}\n                {%- endif %}\n                {%- if do_vision_count %}\n                    {%- set video_count.value = video_count.value + 1 %}\n                {%- endif %}\n                {%- if add_vision_id %}\n                    {{- 'Video ' ~ video_count.value ~ ': ' }}\n                {%- endif %}\n                {{- '<|vision_start|><|video_pad|><|vision_end|>' }}\n            {%- elif 'text' in item %}\n                {{- item.text }}\n            {%- else %}\n                {{- raise_exception('Unexpected item type in content.') }}\n            {%- endif %}\n        {%- endfor %}\n    {%- elif content is none or content is undefined %}\n        {{- '' }}\n    {%- else %}\n        {{- raise_exception('Unexpected content type.') }}\n    {%- endif %}\n{%- endmacro %}\n{%- if not messages %}\n    {{- raise_exception('No messages provided.') }}\n{%- endif %}\n{%- set reasoning_instructions = '' %}\n{%- if enable_thinking is undefined or enable_thinking is true %}\n    {%- set resolved_reasoning_effort = reasoning_effort|default('xhigh') %}\n    {%- if resolved_reasoning_effort not in ('xhigh', 'medium', 'low') %}\n        {{- raise_exception('Unexpected reasoning effort ' ~ reasoning_effort ~ '. Supported types are xhigh (default), medium, and low.') }}\n    {%- endif %}\n    {%- if resolved_reasoning_effort == 'xhigh' %}\n        {%- set reasoning_instructions = 'Reasoning effort is set to xhigh. Please think carefully through the task, validate key assumptions, consider plausible alternatives, and prioritize correctness, consistency, and clarity in the final answer.' %}\n    {%- elif resolved_reasoning_effort == 'low' %}\n        {%- set reasoning_instructions = 'Reasoning effort is set to low. Keep your thinking brief and focused, moving directly to the conclusion without unnecessary elaboration.' %}\n    {%- endif %}\n{%- endif %}\n{%- if tools and tools is iterable and tools is not mapping %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if reasoning_instructions %}\n        {{- reasoning_instructions + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou have access to the following functions:\\n\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\" }}\n    {{- '\\n\\nIf you choose to call a function ONLY reply in the following format with NO suffix:\\n\\n<tool_call>\\n<function=example_function_name>\\n<parameter=example_parameter_1>\\nvalue_1\\n</parameter>\\n<parameter=example_parameter_2>\\nThis is the value for the second parameter\\nthat can span\\nmultiple lines\\n</parameter>\\n</function>\\n</tool_call>\\n\\n<IMPORTANT>\\nReminder:\\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\\n- Required parameters MUST be specified\\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\\n</IMPORTANT>' }}\n    {%- if messages[0].role == 'system' %}\n        {%- set content = render_content(messages[0].content, false, true)|trim %}\n        {%- if content %}\n            {{- '\\n\\n' + content }}\n        {%- endif %}\n    {%- endif %}\n    {{- '<|im_end|>\\n' }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {%- set content = render_content(messages[0].content, false, true)|trim %}\n        {%- if content %}\n            {{- '<|im_start|>system\\n' + (reasoning_instructions + '\\n\\n' if reasoning_instructions else '')  + content + '<|im_end|>\\n' }}\n        {%- elif reasoning_instructions %}\n            {{- '<|im_start|>system\\n' + reasoning_instructions + '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- elif reasoning_instructions %}\n        {{- '<|im_start|>system\\n' + reasoning_instructions + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n    {%- set index = (messages|length - 1) - loop.index0 %}\n    {%- if ns.multi_step_tool and message.role == \"user\" %}\n        {%- set content = render_content(message.content, false)|trim %}\n        {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}\n            {%- set ns.multi_step_tool = false %}\n            {%- set ns.last_query_index = index %}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if ns.multi_step_tool %}\n    {{- raise_exception('No user query found in messages.') }}\n{%- endif %}\n{%- for message in messages %}\n    {%- set content = render_content(message.content, true)|trim %}\n    {%- if message.role == \"system\" %}\n        {%- if not loop.first %}\n            {{- raise_exception('System message must be at the beginning.') }}\n        {%- endif %}\n    {%- elif message.role == \"user\" %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {%- set reasoning_content = '' %}\n        {%- if message.reasoning_content is string %}\n            {%- set reasoning_content = message.reasoning_content %}\n        {%- endif %}\n        {%- set reasoning_content = reasoning_content|trim %}\n        {%- if preserve_thinking is undefined or preserve_thinking is true or loop.index0 > ns.last_query_index %}\n            {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content + '\\n</think>\\n\\n' + content }}\n        {%- else %}\n            {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- endif %}\n        {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if tool_call.function is defined %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {%- if loop.first %}\n                    {%- if content|trim %}\n                        {{- '\\n\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                    {%- else %}\n                        {{- '<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                    {%- endif %}\n                {%- else %}\n                    {{- '\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                {%- endif %}\n                {%- if tool_call.arguments is defined and tool_call.arguments != '' %}\n                    {%- for args_name, args_value in tool_call.arguments|items %}\n                        {{- '<parameter=' + args_name + '>\\n' }}\n                        {%- set args_value = args_value | string if args_value is string else args_value | tojson | safe %}\n                        {{- args_value }}\n                        {{- '\\n</parameter>\\n' }}\n                    {%- endfor %}\n                {%- endif %}\n                {{- '</function>\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.previtem and loop.previtem.role != \"tool\" %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if not loop.last and loop.nextitem.role != \"tool\" %}\n            {{- '<|im_end|>\\n' }}\n        {%- elif loop.last %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- else %}\n        {{- raise_exception('Unexpected message role.') }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n    {%- if enable_thinking is defined and enable_thinking is false %}\n        {{- '<think>\\n\\n</think>\\n\\n' }}\n    {%- else %}\n        {{- '<think>\\n' }}\n    {%- endif %}\n{%- endif %}",
    "model_type": "qwen3_5_text",
    "tokenizer_config": {
      "bos_token": null,
      "eos_token": "<|im_end|>",
      "pad_token": "<|endoftext|>",
      "unk_token": null
    }
  },
  "createdAt": "2026-09-25T12:58:37.000Z",
  "disabled": false,
  "downloads": 1012,
  "gated": false,
  "id": "autotrust/JEV-27B",
  "lastModified": "2026-10-01T03:59:46.000Z",
  "library_name": "transformers",
  "likes": 23,
  "model-index": [
    {
      "name": "autotrust/JEV-27B (student of TypeSafe Jev 1.13)",
      "results": [
        {
          "dataset": {
            "name": "jev-distill-corpus-v3 · test_set_30k",
            "split": "test_set_30k",
            "type": "SargeDev/jev-distill-corpus-v3"
          },
          "metrics": [
            {
              "name": "mean KL(target ‖ model), all test rows (25,376 of 29,955 targets are TypeSafe Jev 1.13 distributions)",
              "type": "kl_divergence",
              "value": 0.0186,
              "verified": false
            },
            {
              "name": "noul AUROC",
              "type": "auroc",
              "value": 0.996,
              "verified": false
            },
            {
              "name": "noul Brier (vs. target probability, all rows)",
              "type": "brier",
              "value": 0.0013,
              "verified": false
            },
            {
              "name": "score expected-value MAE (0–5 scale)",
              "type": "mae",
              "value": 0.098,
              "verified": false
            },
            {
              "name": "ECE (15 bins, after temperature)",
              "type": "ece",
              "value": 0.0009,
              "verified": false
            },
            {
              "name": "choice top-1 agreement (all rows)",
              "type": "accuracy",
              "value": 0.903,
              "verified": false
            },
            {
              "name": "choice top-1 agreement (decisive-target rows, top-2 gap ≥ 0.1)",
              "type": "accuracy",
              "value": 0.958,
              "verified": false
            }
          ],
          "task": {
            "name": "typed decisions (noul / choice / score) — agreement with the TypeSafe Jev 1.13 teacher",
            "type": "text-classification"
          }
        },
        {
          "dataset": {
            "name": "HumanEval",
            "split": "test",
            "type": "openai/openai_humaneval"
          },
          "metrics": [
            {
              "name": "pass@1 (greedy, completion-style prompt)",
              "type": "pass@1",
              "value": 0.78,
              "verified": false
            }
          ],
          "task": {
            "name": "code generation — System 2 path (base lm_head, adapter off)",
            "type": "text-generation"
          }
        }
      ]
    }
  ],
  "modelId": "autotrust/JEV-27B",
  "pipeline_tag": "text-classification",
  "private": false,
  "safetensors": {
    "parameters": {
      "BF16": 26895998464
    },
    "total": 26895998464
  },
  "sha": "962701f3e5437ef5d7cceedae98741477007d367",
  "siblings": [
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      "rfilename": ".gitattributes"
    },
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    },
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      "rfilename": "27b1.jpg"
    },
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      "rfilename": "README.md"
    },
    {
      "rfilename": "adapter/README.md"
    },
    {
      "rfilename": "adapter/adapter_config.json"
    },
    {
      "rfilename": "adapter/adapter_model.safetensors"
    },
    {
      "rfilename": "adapter_vllm/adapter_config.json"
    },
    {
      "rfilename": "adapter_vllm/adapter_model.safetensors"
    },
    {
      "rfilename": "adapter_vllm/decision_head.json"
    },
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      "rfilename": "calibration.json"
    },
    {
      "rfilename": "chat_template.jinja"
    },
    {
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      "rfilename": "judge_config.json"
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    {
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    },
    {
      "rfilename": "reports/b0_qwen35_9b.md"
    },
    {
      "rfilename": "reports/b0_qwen38_27b.md"
    },
    {
      "rfilename": "reports/data_audit.md"
    },
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    },
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      "rfilename": "reports/eval_s2_27b.md"
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    },
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    {
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    {
      "rfilename": "reports/humaneval_vllm_9b.json"
    },
    {
      "rfilename": "reports/m0_qwen35_9b.md"
    },
    {
      "rfilename": "reports/realworld_27b.json"
    },
    {
      "rfilename": "reports/realworld_9b.json"
    },
    {
      "rfilename": "reports/review/step0500.md"
    },
    {
      "rfilename": "reports/review/step0500_27b.md"
    },
    {
      "rfilename": "reports/review/step1500.md"
    },
    {
      "rfilename": "reports/review/step2000_27b.md"
    },
    {
      "rfilename": "reports/review/step2500.md"
    },
    {
      "rfilename": "reports/vllm_decisions_27b.json"
    },
    {
      "rfilename": "reports/vllm_decisions_9b.json"
    },
    {
      "rfilename": "reports/vllm_openai_9b.json"
    },
    {
      "rfilename": "reports/vllm_openai_9b_c256.json"
    },
    {
      "rfilename": "serve_decide.py"
    },
    {
      "rfilename": "tokenizer.json"
    },
    {
      "rfilename": "tokenizer_config.json"
    }
  ],
  "spaces": [
    "autotrust/jev-9b-decision-demo",
    "hugging-apps/jev-27b-vl",
    "autotrust/JEV-27B-Demo"
  ],
  "tags": [
    "transformers",
    "safetensors",
    "qwen3_5_text",
    "text-generation",
    "system-one",
    "system-two",
    "blocks-of-experts",
    "typed-decisions",
    "decision-model",
    "calibrated-probabilities",
    "knowledge-distillation",
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—
Base
base
GGUF quantisationsautotrust/JEV-27B
receipt
Source
GGUF quantisations
Its words
autotrust/JEV-27B
Read by
field:cardData.base_model[]
Said since
2026-09-28 11:46 UTC
Last answered
2026-10-02 18:04 UTC
Original
open at the source
What the source handed over
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—
Downloads
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GGUF quantisations796
receipt
Source
GGUF quantisations
Its words
796
Read by
field:downloads
Said since
2026-10-02 12:01 UTC
Last answered
2026-10-02 18:04 UTC
Original
open at the source
2026-10-02 12:01 UTC796
2026-09-28 11:46 UTC15
What the source handed over
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—
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Hugging Face models1012
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Source
Hugging Face models
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1012
Read by
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Said since
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Original
open at the source
What the source handed over
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Supported types are xhigh (default), medium, and low.') }}\n    {%- endif %}\n    {%- if resolved_reasoning_effort == 'xhigh' %}\n        {%- set reasoning_instructions = 'Reasoning effort is set to xhigh. Please think carefully through the task, validate key assumptions, consider plausible alternatives, and prioritize correctness, consistency, and clarity in the final answer.' %}\n    {%- elif resolved_reasoning_effort == 'low' %}\n        {%- set reasoning_instructions = 'Reasoning effort is set to low. Keep your thinking brief and focused, moving directly to the conclusion without unnecessary elaboration.' %}\n    {%- endif %}\n{%- endif %}\n{%- if tools and tools is iterable and tools is not mapping %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if reasoning_instructions %}\n        {{- reasoning_instructions + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou have access to the following functions:\\n\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\" }}\n    {{- '\\n\\nIf you choose to call a function ONLY reply in the following format with NO suffix:\\n\\n<tool_call>\\n<function=example_function_name>\\n<parameter=example_parameter_1>\\nvalue_1\\n</parameter>\\n<parameter=example_parameter_2>\\nThis is the value for the second parameter\\nthat can span\\nmultiple lines\\n</parameter>\\n</function>\\n</tool_call>\\n\\n<IMPORTANT>\\nReminder:\\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\\n- Required parameters MUST be specified\\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\\n</IMPORTANT>' }}\n    {%- if messages[0].role == 'system' %}\n        {%- set content = render_content(messages[0].content, false, true)|trim %}\n        {%- if content %}\n            {{- '\\n\\n' + content }}\n        {%- endif %}\n    {%- endif %}\n    {{- '<|im_end|>\\n' }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {%- set content = render_content(messages[0].content, false, true)|trim %}\n        {%- if content %}\n            {{- '<|im_start|>system\\n' + (reasoning_instructions + '\\n\\n' if reasoning_instructions else '')  + content + '<|im_end|>\\n' }}\n        {%- elif reasoning_instructions %}\n            {{- '<|im_start|>system\\n' + reasoning_instructions + '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- elif reasoning_instructions %}\n        {{- '<|im_start|>system\\n' + reasoning_instructions + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 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      "rfilename": "reports/b0_qwen35_9b.md"
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      "rfilename": "reports/b0_qwen38_27b.md"
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      "rfilename": "reports/data_audit.md"
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    {
      "rfilename": "reports/eval_27b_bundle.md"
    },
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      "rfilename": "reports/eval_s2_27b.md"
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    {
      "rfilename": "reports/eval_s2_9b_epoch1.md"
    },
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      "rfilename": "reports/eval_v08_bundle.md"
    },
    {
      "rfilename": "reports/fanout_nopc.json"
    },
    {
      "rfilename": "reports/fanout_pc.json"
    },
    {
      "rfilename": "reports/humaneval_27b_base.json"
    },
    {
      "rfilename": "reports/humaneval_27b_bundle.json"
    },
    {
      "rfilename": "reports/humaneval_base.json"
    },
    {
      "rfilename": "reports/humaneval_base_fp32norm.json"
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      "rfilename": "reports/humaneval_v08.json"
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    {
      "rfilename": "reports/humaneval_vllm_27b.json"
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      "rfilename": "reports/m0_qwen35_9b.md"
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      "rfilename": "reports/realworld_27b.json"
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      "rfilename": "reports/realworld_9b.json"
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      "rfilename": "reports/review/step0500.md"
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      "rfilename": "reports/review/step0500_27b.md"
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      "rfilename": "reports/review/step1500.md"
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      "rfilename": "reports/review/step2000_27b.md"
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      "rfilename": "reports/review/step2500.md"
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      "rfilename": "reports/vllm_decisions_27b.json"
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      "rfilename": "reports/vllm_decisions_9b.json"
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      "rfilename": "reports/vllm_openai_9b.json"
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      "rfilename": "reports/vllm_openai_9b_c256.json"
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      "rfilename": "serve_decide.py"
    },
    {
      "rfilename": "tokenizer.json"
    },
    {
      "rfilename": "tokenizer_config.json"
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  ],
  "spaces": [
    "autotrust/jev-9b-decision-demo",
    "hugging-apps/jev-27b-vl",
    "autotrust/JEV-27B-Demo"
  ],
  "tags": [
    "transformers",
    "safetensors",
    "qwen3_5_text",
    "text-generation",
    "system-one",
    "system-two",
    "blocks-of-experts",
    "typed-decisions",
    "decision-model",
    "calibrated-probabilities",
    "knowledge-distillation",
    "jev",
    "noul",
    "choice",
    "score",
    "lora",
    "qwen3_5",
    "dual-head",
    "vllm",
    "text-classification",
    "en",
    "dataset:SargeDev/jev-distill-corpus-v3",
    "base_model:Qwen/Qwen3.8-27B",
    "base_model:finetune:Qwen/Qwen3.8-27B",
    "license:apache-2.0",
    "model-index",
    "endpoints_compatible",
    "region:us"
  ],
  "transformersInfo": {
    "auto_model": "AutoModelForCausalLM",
    "pipeline_tag": "text-generation",
    "processor": "AutoTokenizer"
  },
  "usedStorage": 54699880449,
  "widgetData": [
    {
      "text": "I like you. I love you"
    }
  ]
}
—
Gated
gated
Hugging Face modelsfalse
receipt
Source
Hugging Face models
Its words
false
Read by
field:gated
Said since
2026-10-02 12:02 UTC
Original
open at the source
What the source handed over
{
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    "language": [
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    "architectures": [
      "Qwen3_5ForCausalLM"
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    "chat_template_jinja": "{%- set image_count = namespace(value=0) %}\n{%- set video_count = namespace(value=0) %}\n{%- macro render_content(content, do_vision_count, is_system_content=false) %}\n    {%- if content is string %}\n        {{- content }}\n    {%- elif content is iterable and content is not mapping %}\n        {%- for item in content %}\n            {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}\n                {%- if is_system_content %}\n                    {{- raise_exception('System message cannot contain images.') }}\n                {%- endif %}\n                {%- if do_vision_count %}\n                    {%- set image_count.value = image_count.value + 1 %}\n                {%- endif %}\n                {%- if add_vision_id %}\n                    {{- 'Picture ' ~ image_count.value ~ ': ' }}\n                {%- endif %}\n                {{- '<|vision_start|><|image_pad|><|vision_end|>' }}\n            {%- elif 'video' in item or item.type == 'video' %}\n                {%- if is_system_content %}\n                    {{- raise_exception('System message cannot contain videos.') }}\n                {%- endif %}\n                {%- if do_vision_count %}\n                    {%- set video_count.value = video_count.value + 1 %}\n                {%- endif %}\n                {%- if add_vision_id %}\n                    {{- 'Video ' ~ video_count.value ~ ': ' }}\n                {%- endif %}\n                {{- '<|vision_start|><|video_pad|><|vision_end|>' }}\n            {%- elif 'text' in item %}\n                {{- item.text }}\n            {%- else %}\n                {{- raise_exception('Unexpected item type in content.') }}\n            {%- endif %}\n        {%- endfor %}\n    {%- elif content is none or content is undefined %}\n        {{- '' }}\n    {%- else %}\n        {{- raise_exception('Unexpected content type.') }}\n    {%- endif %}\n{%- endmacro %}\n{%- if not messages %}\n    {{- raise_exception('No messages provided.') }}\n{%- endif %}\n{%- set reasoning_instructions = '' %}\n{%- if enable_thinking is undefined or enable_thinking is true %}\n    {%- set resolved_reasoning_effort = reasoning_effort|default('xhigh') %}\n    {%- if resolved_reasoning_effort not in ('xhigh', 'medium', 'low') %}\n        {{- raise_exception('Unexpected reasoning effort ' ~ reasoning_effort ~ '. Supported types are xhigh (default), medium, and low.') }}\n    {%- endif %}\n    {%- if resolved_reasoning_effort == 'xhigh' %}\n        {%- set reasoning_instructions = 'Reasoning effort is set to xhigh. Please think carefully through the task, validate key assumptions, consider plausible alternatives, and prioritize correctness, consistency, and clarity in the final answer.' %}\n    {%- elif resolved_reasoning_effort == 'low' %}\n        {%- set reasoning_instructions = 'Reasoning effort is set to low. Keep your thinking brief and focused, moving directly to the conclusion without unnecessary elaboration.' %}\n    {%- endif %}\n{%- endif %}\n{%- if tools and tools is iterable and tools is not mapping %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if reasoning_instructions %}\n        {{- reasoning_instructions + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou have access to the following functions:\\n\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\" }}\n    {{- '\\n\\nIf you choose to call a function ONLY reply in the following format with NO suffix:\\n\\n<tool_call>\\n<function=example_function_name>\\n<parameter=example_parameter_1>\\nvalue_1\\n</parameter>\\n<parameter=example_parameter_2>\\nThis is the value for the second parameter\\nthat can span\\nmultiple lines\\n</parameter>\\n</function>\\n</tool_call>\\n\\n<IMPORTANT>\\nReminder:\\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\\n- Required parameters MUST be specified\\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\\n</IMPORTANT>' }}\n    {%- if messages[0].role == 'system' %}\n        {%- set content = render_content(messages[0].content, false, true)|trim %}\n        {%- if content %}\n            {{- '\\n\\n' + content }}\n        {%- endif %}\n    {%- endif %}\n    {{- '<|im_end|>\\n' }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {%- set content = render_content(messages[0].content, false, true)|trim %}\n        {%- if content %}\n            {{- '<|im_start|>system\\n' + (reasoning_instructions + '\\n\\n' if reasoning_instructions else '')  + content + '<|im_end|>\\n' }}\n        {%- elif reasoning_instructions %}\n            {{- '<|im_start|>system\\n' + reasoning_instructions + '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- elif reasoning_instructions %}\n        {{- '<|im_start|>system\\n' + reasoning_instructions + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n    {%- set index = (messages|length - 1) - loop.index0 %}\n    {%- if ns.multi_step_tool and message.role == \"user\" %}\n        {%- set content = render_content(message.content, false)|trim %}\n        {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}\n            {%- set ns.multi_step_tool = false %}\n            {%- set ns.last_query_index = index %}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if ns.multi_step_tool %}\n    {{- raise_exception('No user query found in messages.') }}\n{%- endif %}\n{%- for message in messages %}\n    {%- set content = render_content(message.content, true)|trim %}\n    {%- if message.role == \"system\" %}\n        {%- if not loop.first %}\n            {{- raise_exception('System message must be at the beginning.') }}\n        {%- endif %}\n    {%- elif message.role == \"user\" %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {%- set reasoning_content = '' %}\n        {%- if message.reasoning_content is string %}\n            {%- set reasoning_content = message.reasoning_content %}\n        {%- endif %}\n        {%- set reasoning_content = reasoning_content|trim %}\n        {%- if preserve_thinking is undefined or preserve_thinking is true or loop.index0 > ns.last_query_index %}\n            {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content + '\\n</think>\\n\\n' + content }}\n        {%- else %}\n            {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- endif %}\n        {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if tool_call.function is defined %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {%- if loop.first %}\n                    {%- if content|trim %}\n                        {{- '\\n\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                    {%- else %}\n                        {{- '<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                    {%- endif %}\n                {%- else %}\n                    {{- '\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                {%- endif %}\n                {%- if tool_call.arguments is defined and tool_call.arguments != '' %}\n                    {%- for args_name, args_value in tool_call.arguments|items %}\n                        {{- '<parameter=' + args_name + '>\\n' }}\n                        {%- set args_value = args_value | string if args_value is string else args_value | tojson | safe %}\n                        {{- args_value }}\n                        {{- '\\n</parameter>\\n' }}\n                    {%- endfor %}\n                {%- endif %}\n                {{- '</function>\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.previtem and loop.previtem.role != \"tool\" %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if not loop.last and loop.nextitem.role != \"tool\" %}\n            {{- '<|im_end|>\\n' }}\n        {%- elif loop.last %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- else %}\n        {{- raise_exception('Unexpected message role.') }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n    {%- if enable_thinking is defined and enable_thinking is false %}\n        {{- '<think>\\n\\n</think>\\n\\n' }}\n    {%- else %}\n        {{- '<think>\\n' }}\n    {%- endif %}\n{%- endif %}",
    "model_type": "qwen3_5_text",
    "tokenizer_config": {
      "bos_token": null,
      "eos_token": "<|im_end|>",
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    }
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  "createdAt": "2026-09-25T12:58:37.000Z",
  "disabled": false,
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  "lastModified": "2026-10-01T03:59:46.000Z",
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  "likes": 23,
  "model-index": [
    {
      "name": "autotrust/JEV-27B (student of TypeSafe Jev 1.13)",
      "results": [
        {
          "dataset": {
            "name": "jev-distill-corpus-v3 · test_set_30k",
            "split": "test_set_30k",
            "type": "SargeDev/jev-distill-corpus-v3"
          },
          "metrics": [
            {
              "name": "mean KL(target ‖ model), all test rows (25,376 of 29,955 targets are TypeSafe Jev 1.13 distributions)",
              "type": "kl_divergence",
              "value": 0.0186,
              "verified": false
            },
            {
              "name": "noul AUROC",
              "type": "auroc",
              "value": 0.996,
              "verified": false
            },
            {
              "name": "noul Brier (vs. target probability, all rows)",
              "type": "brier",
              "value": 0.0013,
              "verified": false
            },
            {
              "name": "score expected-value MAE (0–5 scale)",
              "type": "mae",
              "value": 0.098,
              "verified": false
            },
            {
              "name": "ECE (15 bins, after temperature)",
              "type": "ece",
              "value": 0.0009,
              "verified": false
            },
            {
              "name": "choice top-1 agreement (all rows)",
              "type": "accuracy",
              "value": 0.903,
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            },
            {
              "name": "choice top-1 agreement (decisive-target rows, top-2 gap ≥ 0.1)",
              "type": "accuracy",
              "value": 0.958,
              "verified": false
            }
          ],
          "task": {
            "name": "typed decisions (noul / choice / score) — agreement with the TypeSafe Jev 1.13 teacher",
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        },
        {
          "dataset": {
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              "name": "pass@1 (greedy, completion-style prompt)",
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              "value": 0.78,
              "verified": false
            }
          ],
          "task": {
            "name": "code generation — System 2 path (base lm_head, adapter off)",
            "type": "text-generation"
          }
        }
      ]
    }
  ],
  "modelId": "autotrust/JEV-27B",
  "pipeline_tag": "text-classification",
  "private": false,
  "safetensors": {
    "parameters": {
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  "usedStorage": 54699880449,
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      "text": "I like you. I love you"
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}
—
Licence
licence
GGUF quantisationsapache-2.0
receipt
Source
GGUF quantisations
Its words
apache-2.0
Read by
field:cardData.license
Said since
2026-09-28 11:46 UTC
Last answered
2026-10-02 18:04 UTC
Original
open at the source
What the source handed over
{
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  ]
}
—
Licence
licence
Hugging Face modelsapache-2.0
receipt
Source
Hugging Face models
Its words
apache-2.0
Read by
field:cardData.license
Said since
2026-10-02 12:02 UTC
Original
open at the source
What the source handed over
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Supported types are xhigh (default), medium, and low.') }}\n    {%- endif %}\n    {%- if resolved_reasoning_effort == 'xhigh' %}\n        {%- set reasoning_instructions = 'Reasoning effort is set to xhigh. Please think carefully through the task, validate key assumptions, consider plausible alternatives, and prioritize correctness, consistency, and clarity in the final answer.' %}\n    {%- elif resolved_reasoning_effort == 'low' %}\n        {%- set reasoning_instructions = 'Reasoning effort is set to low. Keep your thinking brief and focused, moving directly to the conclusion without unnecessary elaboration.' %}\n    {%- endif %}\n{%- endif %}\n{%- if tools and tools is iterable and tools is not mapping %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if reasoning_instructions %}\n        {{- reasoning_instructions + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou have access to the following functions:\\n\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\" }}\n    {{- '\\n\\nIf you choose to call a function ONLY reply in the following format with NO suffix:\\n\\n<tool_call>\\n<function=example_function_name>\\n<parameter=example_parameter_1>\\nvalue_1\\n</parameter>\\n<parameter=example_parameter_2>\\nThis is the value for the second parameter\\nthat can span\\nmultiple lines\\n</parameter>\\n</function>\\n</tool_call>\\n\\n<IMPORTANT>\\nReminder:\\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\\n- Required parameters MUST be specified\\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\\n</IMPORTANT>' }}\n    {%- if messages[0].role == 'system' %}\n        {%- set content = render_content(messages[0].content, false, true)|trim %}\n        {%- if content %}\n            {{- '\\n\\n' + content }}\n        {%- endif %}\n    {%- endif %}\n    {{- '<|im_end|>\\n' }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {%- set content = render_content(messages[0].content, false, true)|trim %}\n        {%- if content %}\n            {{- '<|im_start|>system\\n' + (reasoning_instructions + '\\n\\n' if reasoning_instructions else '')  + content + '<|im_end|>\\n' }}\n        {%- elif reasoning_instructions %}\n            {{- '<|im_start|>system\\n' + reasoning_instructions + '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- elif reasoning_instructions %}\n        {{- '<|im_start|>system\\n' + reasoning_instructions + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n    {%- set index = (messages|length - 1) - loop.index0 %}\n    {%- if ns.multi_step_tool and message.role == \"user\" %}\n        {%- set content = render_content(message.content, false)|trim %}\n        {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}\n            {%- set ns.multi_step_tool = false %}\n            {%- set ns.last_query_index = index %}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if ns.multi_step_tool %}\n    {{- raise_exception('No user query found in messages.') }}\n{%- endif %}\n{%- for message in messages %}\n    {%- set content = render_content(message.content, true)|trim %}\n    {%- if message.role == \"system\" %}\n        {%- if not loop.first %}\n            {{- raise_exception('System message must be at the beginning.') }}\n        {%- endif %}\n    {%- elif message.role == \"user\" %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {%- set reasoning_content = '' %}\n        {%- if message.reasoning_content is string %}\n            {%- set reasoning_content = message.reasoning_content %}\n        {%- endif %}\n        {%- set reasoning_content = reasoning_content|trim %}\n        {%- if preserve_thinking is undefined or preserve_thinking is true or loop.index0 > ns.last_query_index %}\n            {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content + '\\n</think>\\n\\n' + content }}\n        {%- else %}\n            {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- endif %}\n        {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if tool_call.function is defined %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {%- if loop.first %}\n                    {%- if content|trim %}\n                        {{- '\\n\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                    {%- else %}\n                        {{- '<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                    {%- endif %}\n                {%- else %}\n                    {{- '\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                {%- endif %}\n                {%- if tool_call.arguments is defined and tool_call.arguments != '' %}\n                    {%- for args_name, args_value in tool_call.arguments|items %}\n                        {{- '<parameter=' + args_name + '>\\n' }}\n                        {%- set args_value = args_value | string if args_value is string else args_value | tojson | safe %}\n                        {{- args_value }}\n                        {{- '\\n</parameter>\\n' }}\n                    {%- endfor %}\n                {%- endif %}\n                {{- '</function>\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.previtem and loop.previtem.role != \"tool\" %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if not loop.last and loop.nextitem.role != \"tool\" %}\n            {{- '<|im_end|>\\n' }}\n        {%- elif loop.last %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- else %}\n        {{- raise_exception('Unexpected message role.') }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n    {%- if enable_thinking is defined and enable_thinking is false %}\n        {{- '<think>\\n\\n</think>\\n\\n' }}\n    {%- else %}\n        {{- '<think>\\n' }}\n    {%- endif %}\n{%- endif %}",
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  "model-index": [
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              "verified": false
            },
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              "value": 0.996,
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              "verified": false
            }
          ],
          "task": {
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  "modelId": "autotrust/JEV-27B",
  "pipeline_tag": "text-classification",
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      "rfilename": "reports/humaneval_base.json"
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      "rfilename": "reports/humaneval_base_fp32norm.json"
    },
    {
      "rfilename": "reports/humaneval_v08.json"
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    {
      "rfilename": "reports/humaneval_v08_bundle.json"
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    {
      "rfilename": "reports/humaneval_vllm_27b.json"
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      "rfilename": "reports/humaneval_vllm_9b.json"
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    {
      "rfilename": "reports/m0_qwen35_9b.md"
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      "rfilename": "reports/realworld_27b.json"
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      "rfilename": "reports/review/step0500.md"
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      "rfilename": "reports/vllm_decisions_27b.json"
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      "rfilename": "reports/vllm_decisions_9b.json"
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      "rfilename": "reports/vllm_openai_9b.json"
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    "autotrust/jev-9b-decision-demo",
    "hugging-apps/jev-27b-vl",
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  ],
  "tags": [
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    "score",
    "lora",
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    "dual-head",
    "vllm",
    "text-classification",
    "en",
    "dataset:SargeDev/jev-distill-corpus-v3",
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    "base_model:finetune:Qwen/Qwen3.8-27B",
    "license:apache-2.0",
    "model-index",
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  },
  "usedStorage": 54699880449,
  "widgetData": [
    {
      "text": "I like you. I love you"
    }
  ]
}
—
Likes
likes
not compared
GGUF quantisations2
receipt
Source
GGUF quantisations
Its words
2
Read by
field:likes
Said since
2026-10-02 12:01 UTC
Last answered
2026-10-02 18:04 UTC
Original
open at the source
2026-10-02 12:01 UTC2
2026-09-28 11:46 UTC1
What the source handed over
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      "autotrust/JEV-27B"
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  "createdAt": "2026-09-28T04:25:42.000Z",
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    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ]
}
—
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Hugging Face models23
receipt
Source
Hugging Face models
Its words
23
Read by
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Said since
2026-10-02 12:02 UTC
Original
open at the source
What the source handed over
{
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Supported types are xhigh (default), medium, and low.') }}\n    {%- endif %}\n    {%- if resolved_reasoning_effort == 'xhigh' %}\n        {%- set reasoning_instructions = 'Reasoning effort is set to xhigh. Please think carefully through the task, validate key assumptions, consider plausible alternatives, and prioritize correctness, consistency, and clarity in the final answer.' %}\n    {%- elif resolved_reasoning_effort == 'low' %}\n        {%- set reasoning_instructions = 'Reasoning effort is set to low. Keep your thinking brief and focused, moving directly to the conclusion without unnecessary elaboration.' %}\n    {%- endif %}\n{%- endif %}\n{%- if tools and tools is iterable and tools is not mapping %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if reasoning_instructions %}\n        {{- reasoning_instructions + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou have access to the following functions:\\n\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\" }}\n    {{- '\\n\\nIf you choose to call a function ONLY reply in the following format with NO suffix:\\n\\n<tool_call>\\n<function=example_function_name>\\n<parameter=example_parameter_1>\\nvalue_1\\n</parameter>\\n<parameter=example_parameter_2>\\nThis is the value for the second parameter\\nthat can span\\nmultiple lines\\n</parameter>\\n</function>\\n</tool_call>\\n\\n<IMPORTANT>\\nReminder:\\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\\n- Required parameters MUST be specified\\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\\n</IMPORTANT>' }}\n    {%- if messages[0].role == 'system' %}\n        {%- set content = render_content(messages[0].content, false, true)|trim %}\n        {%- if content %}\n            {{- '\\n\\n' + content }}\n        {%- endif %}\n    {%- endif %}\n    {{- '<|im_end|>\\n' }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {%- set content = render_content(messages[0].content, false, true)|trim %}\n        {%- if content %}\n            {{- '<|im_start|>system\\n' + (reasoning_instructions + '\\n\\n' if reasoning_instructions else '')  + content + '<|im_end|>\\n' }}\n        {%- elif reasoning_instructions %}\n            {{- '<|im_start|>system\\n' + reasoning_instructions + '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- elif reasoning_instructions %}\n        {{- '<|im_start|>system\\n' + reasoning_instructions + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n    {%- set index = (messages|length - 1) - loop.index0 %}\n    {%- if ns.multi_step_tool and message.role == \"user\" %}\n        {%- set content = render_content(message.content, false)|trim %}\n        {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}\n            {%- set ns.multi_step_tool = false %}\n            {%- set ns.last_query_index = index %}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if ns.multi_step_tool %}\n    {{- raise_exception('No user query found in messages.') }}\n{%- endif %}\n{%- for message in messages %}\n    {%- set content = render_content(message.content, true)|trim %}\n    {%- if message.role == \"system\" %}\n        {%- if not loop.first %}\n            {{- raise_exception('System message must be at the beginning.') }}\n        {%- endif %}\n    {%- elif message.role == \"user\" %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {%- set reasoning_content = '' %}\n        {%- if message.reasoning_content is string %}\n            {%- set reasoning_content = message.reasoning_content %}\n        {%- endif %}\n        {%- set reasoning_content = reasoning_content|trim %}\n        {%- if preserve_thinking is undefined or preserve_thinking is true or loop.index0 > ns.last_query_index %}\n            {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content + '\\n</think>\\n\\n' + content }}\n        {%- else %}\n            {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- endif %}\n        {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if tool_call.function is defined %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {%- if loop.first %}\n                    {%- if content|trim %}\n                        {{- '\\n\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                    {%- else %}\n                        {{- '<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                    {%- endif %}\n                {%- else %}\n                    {{- '\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                {%- endif %}\n                {%- if tool_call.arguments is defined and tool_call.arguments != '' %}\n                    {%- for args_name, args_value in tool_call.arguments|items %}\n                        {{- '<parameter=' + args_name + '>\\n' }}\n                        {%- set args_value = args_value | string if args_value is string else args_value | tojson | safe %}\n                        {{- args_value }}\n                        {{- '\\n</parameter>\\n' }}\n                    {%- endfor %}\n                {%- endif %}\n                {{- '</function>\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.previtem and loop.previtem.role != \"tool\" %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if not loop.last and loop.nextitem.role != \"tool\" %}\n            {{- '<|im_end|>\\n' }}\n        {%- elif loop.last %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- else %}\n        {{- raise_exception('Unexpected message role.') }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n    {%- if enable_thinking is defined and enable_thinking is false %}\n        {{- '<think>\\n\\n</think>\\n\\n' }}\n    {%- else %}\n        {{- '<think>\\n' }}\n    {%- endif %}\n{%- endif %}",
    "model_type": "qwen3_5_text",
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      "eos_token": "<|im_end|>",
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  "createdAt": "2026-09-25T12:58:37.000Z",
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  "downloads": 1012,
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  "lastModified": "2026-10-01T03:59:46.000Z",
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  "likes": 23,
  "model-index": [
    {
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      "results": [
        {
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            "split": "test_set_30k",
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          },
          "metrics": [
            {
              "name": "mean KL(target ‖ model), all test rows (25,376 of 29,955 targets are TypeSafe Jev 1.13 distributions)",
              "type": "kl_divergence",
              "value": 0.0186,
              "verified": false
            },
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              "name": "noul AUROC",
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              "value": 0.996,
              "verified": false
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              "name": "noul Brier (vs. target probability, all rows)",
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              "value": 0.0013,
              "verified": false
            },
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              "name": "score expected-value MAE (0–5 scale)",
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              "value": 0.098,
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              "name": "ECE (15 bins, after temperature)",
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              "type": "accuracy",
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              "verified": false
            }
          ],
          "task": {
            "name": "typed decisions (noul / choice / score) — agreement with the TypeSafe Jev 1.13 teacher",
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              "verified": false
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          "task": {
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  "modelId": "autotrust/JEV-27B",
  "pipeline_tag": "text-classification",
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  "safetensors": {
    "parameters": {
      "BF16": 26895998464
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      "rfilename": "reports/data_audit.md"
    },
    {
      "rfilename": "reports/eval_27b_bundle.md"
    },
    {
      "rfilename": "reports/eval_s2_27b.md"
    },
    {
      "rfilename": "reports/eval_s2_9b.md"
    },
    {
      "rfilename": "reports/eval_s2_9b_epoch1.md"
    },
    {
      "rfilename": "reports/eval_v08_bundle.md"
    },
    {
      "rfilename": "reports/fanout_nopc.json"
    },
    {
      "rfilename": "reports/fanout_pc.json"
    },
    {
      "rfilename": "reports/humaneval_27b_base.json"
    },
    {
      "rfilename": "reports/humaneval_27b_bundle.json"
    },
    {
      "rfilename": "reports/humaneval_base.json"
    },
    {
      "rfilename": "reports/humaneval_base_fp32norm.json"
    },
    {
      "rfilename": "reports/humaneval_v08.json"
    },
    {
      "rfilename": "reports/humaneval_v08_bundle.json"
    },
    {
      "rfilename": "reports/humaneval_vllm_27b.json"
    },
    {
      "rfilename": "reports/humaneval_vllm_9b.json"
    },
    {
      "rfilename": "reports/m0_qwen35_9b.md"
    },
    {
      "rfilename": "reports/realworld_27b.json"
    },
    {
      "rfilename": "reports/realworld_9b.json"
    },
    {
      "rfilename": "reports/review/step0500.md"
    },
    {
      "rfilename": "reports/review/step0500_27b.md"
    },
    {
      "rfilename": "reports/review/step1500.md"
    },
    {
      "rfilename": "reports/review/step2000_27b.md"
    },
    {
      "rfilename": "reports/review/step2500.md"
    },
    {
      "rfilename": "reports/vllm_decisions_27b.json"
    },
    {
      "rfilename": "reports/vllm_decisions_9b.json"
    },
    {
      "rfilename": "reports/vllm_openai_9b.json"
    },
    {
      "rfilename": "reports/vllm_openai_9b_c256.json"
    },
    {
      "rfilename": "serve_decide.py"
    },
    {
      "rfilename": "tokenizer.json"
    },
    {
      "rfilename": "tokenizer_config.json"
    }
  ],
  "spaces": [
    "autotrust/jev-9b-decision-demo",
    "hugging-apps/jev-27b-vl",
    "autotrust/JEV-27B-Demo"
  ],
  "tags": [
    "transformers",
    "safetensors",
    "qwen3_5_text",
    "text-generation",
    "system-one",
    "system-two",
    "blocks-of-experts",
    "typed-decisions",
    "decision-model",
    "calibrated-probabilities",
    "knowledge-distillation",
    "jev",
    "noul",
    "choice",
    "score",
    "lora",
    "qwen3_5",
    "dual-head",
    "vllm",
    "text-classification",
    "en",
    "dataset:SargeDev/jev-distill-corpus-v3",
    "base_model:Qwen/Qwen3.8-27B",
    "base_model:finetune:Qwen/Qwen3.8-27B",
    "license:apache-2.0",
    "model-index",
    "endpoints_compatible",
    "region:us"
  ],
  "transformersInfo": {
    "auto_model": "AutoModelForCausalLM",
    "pipeline_tag": "text-generation",
    "processor": "AutoTokenizer"
  },
  "usedStorage": 54699880449,
  "widgetData": [
    {
      "text": "I like you. I love you"
    }
  ]
}
—
Task
task
Hugging Face modelstext-classification
receipt
Source
Hugging Face models
Its words
text-classification
Read by
field:pipeline_tag
Said since
2026-10-02 12:02 UTC
Original
open at the source
What the source handed over
{
  "_asked": "autotrust/JEV-27B",
  "_id": "6ab66ffdf7bd8732d74b7264",
  "author": "autotrust",
  "cardData": {
    "base_model": "Qwen/Qwen3.8-27B",
    "base_model_relation": "finetune",
    "datasets": [
      "SargeDev/jev-distill-corpus-v3"
    ],
    "language": [
      "en"
    ],
    "library_name": "transformers",
    "license": "apache-2.0",
    "metrics": [
      "kl",
      "auroc",
      "brier",
      "ece"
    ],
    "model-index": [
      {
        "name": "autotrust/JEV-27B (student of TypeSafe Jev 1.13)",
        "results": [
          {
            "dataset": {
              "name": "jev-distill-corpus-v3 · test_set_30k",
              "split": "test_set_30k",
              "type": "SargeDev/jev-distill-corpus-v3"
            },
            "metrics": [
              {
                "name": "mean KL(target ‖ model), all test rows (25,376 of 29,955 targets are TypeSafe Jev 1.13 distributions)",
                "type": "kl_divergence",
                "value": 0.0186,
                "verified": false
              },
              {
                "name": "noul AUROC",
                "type": "auroc",
                "value": 0.996,
                "verified": false
              },
              {
                "name": "noul Brier (vs. target probability, all rows)",
                "type": "brier",
                "value": 0.0013,
                "verified": false
              },
              {
                "name": "score expected-value MAE (0–5 scale)",
                "type": "mae",
                "value": 0.098,
                "verified": false
              },
              {
                "name": "ECE (15 bins, after temperature)",
                "type": "ece",
                "value": 0.0009,
                "verified": false
              },
              {
                "name": "choice top-1 agreement (all rows)",
                "type": "accuracy",
                "value": 0.903,
                "verified": false
              },
              {
                "name": "choice top-1 agreement (decisive-target rows, top-2 gap ≥ 0.1)",
                "type": "accuracy",
                "value": 0.958,
                "verified": false
              }
            ],
            "task": {
              "name": "typed decisions (noul / choice / score) — agreement with the TypeSafe Jev 1.13 teacher",
              "type": "text-classification"
            }
          },
          {
            "dataset": {
              "name": "HumanEval",
              "split": "test",
              "type": "openai/openai_humaneval"
            },
            "metrics": [
              {
                "name": "pass@1 (greedy, completion-style prompt)",
                "type": "pass@1",
                "value": 0.78,
                "verified": false
              }
            ],
            "task": {
              "name": "code generation — System 2 path (base lm_head, adapter off)",
              "type": "text-generation"
            }
          }
        ]
      }
    ],
    "pipeline_tag": "text-classification",
    "tags": [
      "system-one",
      "system-two",
      "blocks-of-experts",
      "typed-decisions",
      "decision-model",
      "calibrated-probabilities",
      "knowledge-distillation",
      "jev",
      "noul",
      "choice",
      "score",
      "lora",
      "qwen3_5",
      "text-generation",
      "dual-head",
      "vllm"
    ]
  },
  "config": {
    "architectures": [
      "Qwen3_5ForCausalLM"
    ],
    "chat_template_jinja": "{%- set image_count = namespace(value=0) %}\n{%- set video_count = namespace(value=0) %}\n{%- macro render_content(content, do_vision_count, is_system_content=false) %}\n    {%- if content is string %}\n        {{- content }}\n    {%- elif content is iterable and content is not mapping %}\n        {%- for item in content %}\n            {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}\n                {%- if is_system_content %}\n                    {{- raise_exception('System message cannot contain images.') }}\n                {%- endif %}\n                {%- if do_vision_count %}\n                    {%- set image_count.value = image_count.value + 1 %}\n                {%- endif %}\n                {%- if add_vision_id %}\n                    {{- 'Picture ' ~ image_count.value ~ ': ' }}\n                {%- endif %}\n                {{- '<|vision_start|><|image_pad|><|vision_end|>' }}\n            {%- elif 'video' in item or item.type == 'video' %}\n                {%- if is_system_content %}\n                    {{- raise_exception('System message cannot contain videos.') }}\n                {%- endif %}\n                {%- if do_vision_count %}\n                    {%- set video_count.value = video_count.value + 1 %}\n                {%- endif %}\n                {%- if add_vision_id %}\n                    {{- 'Video ' ~ video_count.value ~ ': ' }}\n                {%- endif %}\n                {{- '<|vision_start|><|video_pad|><|vision_end|>' }}\n            {%- elif 'text' in item %}\n                {{- item.text }}\n            {%- else %}\n                {{- raise_exception('Unexpected item type in content.') }}\n            {%- endif %}\n        {%- endfor %}\n    {%- elif content is none or content is undefined %}\n        {{- '' }}\n    {%- else %}\n        {{- raise_exception('Unexpected content type.') }}\n    {%- endif %}\n{%- endmacro %}\n{%- if not messages %}\n    {{- raise_exception('No messages provided.') }}\n{%- endif %}\n{%- set reasoning_instructions = '' %}\n{%- if enable_thinking is undefined or enable_thinking is true %}\n    {%- set resolved_reasoning_effort = reasoning_effort|default('xhigh') %}\n    {%- if resolved_reasoning_effort not in ('xhigh', 'medium', 'low') %}\n        {{- raise_exception('Unexpected reasoning effort ' ~ reasoning_effort ~ '. Supported types are xhigh (default), medium, and low.') }}\n    {%- endif %}\n    {%- if resolved_reasoning_effort == 'xhigh' %}\n        {%- set reasoning_instructions = 'Reasoning effort is set to xhigh. Please think carefully through the task, validate key assumptions, consider plausible alternatives, and prioritize correctness, consistency, and clarity in the final answer.' %}\n    {%- elif resolved_reasoning_effort == 'low' %}\n        {%- set reasoning_instructions = 'Reasoning effort is set to low. Keep your thinking brief and focused, moving directly to the conclusion without unnecessary elaboration.' %}\n    {%- endif %}\n{%- endif %}\n{%- if tools and tools is iterable and tools is not mapping %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if reasoning_instructions %}\n        {{- reasoning_instructions + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou have access to the following functions:\\n\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\" }}\n    {{- '\\n\\nIf you choose to call a function ONLY reply in the following format with NO suffix:\\n\\n<tool_call>\\n<function=example_function_name>\\n<parameter=example_parameter_1>\\nvalue_1\\n</parameter>\\n<parameter=example_parameter_2>\\nThis is the value for the second parameter\\nthat can span\\nmultiple lines\\n</parameter>\\n</function>\\n</tool_call>\\n\\n<IMPORTANT>\\nReminder:\\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\\n- Required parameters MUST be specified\\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\\n</IMPORTANT>' }}\n    {%- if messages[0].role == 'system' %}\n        {%- set content = render_content(messages[0].content, false, true)|trim %}\n        {%- if content %}\n            {{- '\\n\\n' + content }}\n        {%- endif %}\n    {%- endif %}\n    {{- '<|im_end|>\\n' }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {%- set content = render_content(messages[0].content, false, true)|trim %}\n        {%- if content %}\n            {{- '<|im_start|>system\\n' + (reasoning_instructions + '\\n\\n' if reasoning_instructions else '')  + content + '<|im_end|>\\n' }}\n        {%- elif reasoning_instructions %}\n            {{- '<|im_start|>system\\n' + reasoning_instructions + '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- elif reasoning_instructions %}\n        {{- '<|im_start|>system\\n' + reasoning_instructions + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n    {%- set index = (messages|length - 1) - loop.index0 %}\n    {%- if ns.multi_step_tool and message.role == \"user\" %}\n        {%- set content = render_content(message.content, false)|trim %}\n        {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}\n            {%- set ns.multi_step_tool = false %}\n            {%- set ns.last_query_index = index %}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if ns.multi_step_tool %}\n    {{- raise_exception('No user query found in messages.') }}\n{%- endif %}\n{%- for message in messages %}\n    {%- set content = render_content(message.content, true)|trim %}\n    {%- if message.role == \"system\" %}\n        {%- if not loop.first %}\n            {{- raise_exception('System message must be at the beginning.') }}\n        {%- endif %}\n    {%- elif message.role == \"user\" %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {%- set reasoning_content = '' %}\n        {%- if message.reasoning_content is string %}\n            {%- set reasoning_content = message.reasoning_content %}\n        {%- endif %}\n        {%- set reasoning_content = reasoning_content|trim %}\n        {%- if preserve_thinking is undefined or preserve_thinking is true or loop.index0 > ns.last_query_index %}\n            {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content + '\\n</think>\\n\\n' + content }}\n        {%- else %}\n            {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- endif %}\n        {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if tool_call.function is defined %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {%- if loop.first %}\n                    {%- if content|trim %}\n                        {{- '\\n\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                    {%- else %}\n                        {{- '<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                    {%- endif %}\n                {%- else %}\n                    {{- '\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n                {%- endif %}\n                {%- if tool_call.arguments is defined and tool_call.arguments != '' %}\n                    {%- for args_name, args_value in tool_call.arguments|items %}\n                        {{- '<parameter=' + args_name + '>\\n' }}\n                        {%- set args_value = args_value | string if args_value is string else args_value | tojson | safe %}\n                        {{- args_value }}\n                        {{- '\\n</parameter>\\n' }}\n                    {%- endfor %}\n                {%- endif %}\n                {{- '</function>\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.previtem and loop.previtem.role != \"tool\" %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if not loop.last and loop.nextitem.role != \"tool\" %}\n            {{- '<|im_end|>\\n' }}\n        {%- elif loop.last %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- else %}\n        {{- raise_exception('Unexpected message role.') }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n    {%- if enable_thinking is defined and enable_thinking is false %}\n        {{- '<think>\\n\\n</think>\\n\\n' }}\n    {%- else %}\n        {{- '<think>\\n' }}\n    {%- endif %}\n{%- endif %}",
    "model_type": "qwen3_5_text",
    "tokenizer_config": {
      "bos_token": null,
      "eos_token": "<|im_end|>",
      "pad_token": "<|endoftext|>",
      "unk_token": null
    }
  },
  "createdAt": "2026-09-25T12:58:37.000Z",
  "disabled": false,
  "downloads": 1012,
  "gated": false,
  "id": "autotrust/JEV-27B",
  "lastModified": "2026-10-01T03:59:46.000Z",
  "library_name": "transformers",
  "likes": 23,
  "model-index": [
    {
      "name": "autotrust/JEV-27B (student of TypeSafe Jev 1.13)",
      "results": [
        {
          "dataset": {
            "name": "jev-distill-corpus-v3 · test_set_30k",
            "split": "test_set_30k",
            "type": "SargeDev/jev-distill-corpus-v3"
          },
          "metrics": [
            {
              "name": "mean KL(target ‖ model), all test rows (25,376 of 29,955 targets are TypeSafe Jev 1.13 distributions)",
              "type": "kl_divergence",
              "value": 0.0186,
              "verified": false
            },
            {
              "name": "noul AUROC",
              "type": "auroc",
              "value": 0.996,
              "verified": false
            },
            {
              "name": "noul Brier (vs. target probability, all rows)",
              "type": "brier",
              "value": 0.0013,
              "verified": false
            },
            {
              "name": "score expected-value MAE (0–5 scale)",
              "type": "mae",
              "value": 0.098,
              "verified": false
            },
            {
              "name": "ECE (15 bins, after temperature)",
              "type": "ece",
              "value": 0.0009,
              "verified": false
            },
            {
              "name": "choice top-1 agreement (all rows)",
              "type": "accuracy",
              "value": 0.903,
              "verified": false
            },
            {
              "name": "choice top-1 agreement (decisive-target rows, top-2 gap ≥ 0.1)",
              "type": "accuracy",
              "value": 0.958,
              "verified": false
            }
          ],
          "task": {
            "name": "typed decisions (noul / choice / score) — agreement with the TypeSafe Jev 1.13 teacher",
            "type": "text-classification"
          }
        },
        {
          "dataset": {
            "name": "HumanEval",
            "split": "test",
            "type": "openai/openai_humaneval"
          },
          "metrics": [
            {
              "name": "pass@1 (greedy, completion-style prompt)",
              "type": "pass@1",
              "value": 0.78,
              "verified": false
            }
          ],
          "task": {
            "name": "code generation — System 2 path (base lm_head, adapter off)",
            "type": "text-generation"
          }
        }
      ]
    }
  ],
  "modelId": "autotrust/JEV-27B",
  "pipeline_tag": "text-classification",
  "private": false,
  "safetensors": {
    "parameters": {
      "BF16": 26895998464
    },
    "total": 26895998464
  },
  "sha": "962701f3e5437ef5d7cceedae98741477007d367",
  "siblings": [
    {
      "rfilename": ".gitattributes"
    },
    {
      "rfilename": "27b-2.jpg"
    },
    {
      "rfilename": "27b-3.jpg"
    },
    {
      "rfilename": "27b1.jpg"
    },
    {
      "rfilename": "README.md"
    },
    {
      "rfilename": "adapter/README.md"
    },
    {
      "rfilename": "adapter/adapter_config.json"
    },
    {
      "rfilename": "adapter/adapter_model.safetensors"
    },
    {
      "rfilename": "adapter_vllm/adapter_config.json"
    },
    {
      "rfilename": "adapter_vllm/adapter_model.safetensors"
    },
    {
      "rfilename": "adapter_vllm/decision_head.json"
    },
    {
      "rfilename": "calibration.json"
    },
    {
      "rfilename": "chat_template.jinja"
    },
    {
      "rfilename": "config.json"
    },
    {
      "rfilename": "head.safetensors"
    },
    {
      "rfilename": "judge_config.json"
    },
    {
      "rfilename": "model-00001-of-00013.safetensors"
    },
    {
      "rfilename": "model-00002-of-00013.safetensors"
    },
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    {
      "rfilename": "model-00013-of-00013.safetensors"
    },
    {
      "rfilename": "model.safetensors.index.json"
    },
    {
      "rfilename": "reports/b0_qwen35_9b.md"
    },
    {
      "rfilename": "reports/b0_qwen38_27b.md"
    },
    {
      "rfilename": "reports/data_audit.md"
    },
    {
      "rfilename": "reports/eval_27b_bundle.md"
    },
    {
      "rfilename": "reports/eval_s2_27b.md"
    },
    {
      "rfilename": "reports/eval_s2_9b.md"
    },
    {
      "rfilename": "reports/eval_s2_9b_epoch1.md"
    },
    {
      "rfilename": "reports/eval_v08_bundle.md"
    },
    {
      "rfilename": "reports/fanout_nopc.json"
    },
    {
      "rfilename": "reports/fanout_pc.json"
    },
    {
      "rfilename": "reports/humaneval_27b_base.json"
    },
    {
      "rfilename": "reports/humaneval_27b_bundle.json"
    },
    {
      "rfilename": "reports/humaneval_base.json"
    },
    {
      "rfilename": "reports/humaneval_base_fp32norm.json"
    },
    {
      "rfilename": "reports/humaneval_v08.json"
    },
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      "rfilename": "reports/humaneval_v08_bundle.json"
    },
    {
      "rfilename": "reports/humaneval_vllm_27b.json"
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    },
    {
      "rfilename": "reports/m0_qwen35_9b.md"
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    {
      "rfilename": "reports/realworld_27b.json"
    },
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      "rfilename": "reports/realworld_9b.json"
    },
    {
      "rfilename": "reports/review/step0500.md"
    },
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      "rfilename": "reports/review/step0500_27b.md"
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      "rfilename": "reports/review/step1500.md"
    },
    {
      "rfilename": "reports/review/step2000_27b.md"
    },
    {
      "rfilename": "reports/review/step2500.md"
    },
    {
      "rfilename": "reports/vllm_decisions_27b.json"
    },
    {
      "rfilename": "reports/vllm_decisions_9b.json"
    },
    {
      "rfilename": "reports/vllm_openai_9b.json"
    },
    {
      "rfilename": "reports/vllm_openai_9b_c256.json"
    },
    {
      "rfilename": "serve_decide.py"
    },
    {
      "rfilename": "tokenizer.json"
    },
    {
      "rfilename": "tokenizer_config.json"
    }
  ],
  "spaces": [
    "autotrust/jev-9b-decision-demo",
    "hugging-apps/jev-27b-vl",
    "autotrust/JEV-27B-Demo"
  ],
  "tags": [
    "transformers",
    "safetensors",
    "qwen3_5_text",
    "text-generation",
    "system-one",
    "system-two",
    "blocks-of-experts",
    "typed-decisions",
    "decision-model",
    "calibrated-probabilities",
    "knowledge-distillation",
    "jev",
    "noul",
    "choice",
    "score",
    "lora",
    "qwen3_5",
    "dual-head",
    "vllm",
    "text-classification",
    "en",
    "dataset:SargeDev/jev-distill-corpus-v3",
    "base_model:Qwen/Qwen3.8-27B",
    "base_model:finetune:Qwen/Qwen3.8-27B",
    "license:apache-2.0",
    "model-index",
    "endpoints_compatible",
    "region:us"
  ],
  "transformersInfo": {
    "auto_model": "AutoModelForCausalLM",
    "pipeline_tag": "text-generation",
    "processor": "AutoTokenizer"
  },
  "usedStorage": 54699880449,
  "widgetData": [
    {
      "text": "I like you. I love you"
    }
  ]
}
—

model

autotrust/JEV-27B
zetlyn/models-hf · 2026-09-25
author autotrust downloads 1012 gated false licence apache-2.0 likes 23 task text-classification source

quantisation

prithivMLmods/JEV-27B-GGUF
zetlyn/models-gguf · 2026-09-28
author prithivMLmods base autotrust/JEV-27B downloads 796 licence apache-2.0 likes 2 source