Akahsizrr/Cyber-Prime-1.1-2.6B
hf Akahsizrr/Cyber-Prime-1.1-2.6B 2 sources, 3 claims · Watch
What each source says
| Property | Source | Said | Means here |
|---|---|---|---|
| Author author not compared | GGUF quantisations | mradermacherreceipt
What the source handed over{
"_id": "6ab484a9350763546e86ce3a",
"author": "mradermacher",
"cardData": {
"base_model": "Akahsizrr/Cyber-Prime-1.1-2.6B",
"datasets": [
"jpmorganchase/CyberBench",
"tihanyin/CyberMetric",
"secbench-hf/SecBench",
"XuanwuAI/SecEval"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "other",
"license_link": "LICENSE",
"license_name": "lfm1.0",
"mradermacher": {
"readme_rev": 1
},
"quantized_by": "mradermacher",
"tags": [
"cybersecurity",
"cyberbench",
"threat-intelligence",
"named-entity-recognition",
"phishing-detection",
"http-anomaly-detection",
"lfm2",
"2.6b"
]
},
"createdAt": "2026-09-24T02:02:17.000Z",
"downloads": 637,
"gated": false,
"id": "mradermacher/Cyber-Prime-1.1-2.6B-GGUF",
"lastModified": "2026-09-26T01:03:44.000Z",
"library_name": "transformers",
"likes": 1,
"modelId": "mradermacher/Cyber-Prime-1.1-2.6B-GGUF",
"private": false,
"sha": "95576be097925d3cd711f1014e59679eca2836e1",
"siblings": [
{
"rfilename": ".gitattributes"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.IQ4_XS.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q2_K.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q3_K_L.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q3_K_M.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q3_K_S.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q4_K_M.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q4_K_S.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q5_K_M.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q5_K_S.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q6_K.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q8_0.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.f16.gguf"
},
{
"rfilename": "README.md"
}
],
"tags": [
"transformers",
"gguf",
"cybersecurity",
"cyberbench",
"threat-intelligence",
"named-entity-recognition",
"phishing-detection",
"http-anomaly-detection",
"lfm2",
"2.6b",
"en",
"dataset:jpmorganchase/CyberBench",
"dataset:tihanyin/CyberMetric",
"dataset:secbench-hf/SecBench",
"dataset:XuanwuAI/SecEval",
"base_model:Akahsizrr/Cyber-Prime-1.1-2.6B",
"base_model:quantized:Akahsizrr/Cyber-Prime-1.1-2.6B",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
]
} | — |
| Author author not compared | Hugging Face models | Akahsizrrreceipt
This source has not kept a receipt for this claim yet. The next update that reads it will. | — |
| Base base | GGUF quantisations | Akahsizrr/Cyber-Prime-1.1-2.6Breceipt
What the source handed over{
"_id": "6ab484a9350763546e86ce3a",
"author": "mradermacher",
"cardData": {
"base_model": "Akahsizrr/Cyber-Prime-1.1-2.6B",
"datasets": [
"jpmorganchase/CyberBench",
"tihanyin/CyberMetric",
"secbench-hf/SecBench",
"XuanwuAI/SecEval"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "other",
"license_link": "LICENSE",
"license_name": "lfm1.0",
"mradermacher": {
"readme_rev": 1
},
"quantized_by": "mradermacher",
"tags": [
"cybersecurity",
"cyberbench",
"threat-intelligence",
"named-entity-recognition",
"phishing-detection",
"http-anomaly-detection",
"lfm2",
"2.6b"
]
},
"createdAt": "2026-09-24T02:02:17.000Z",
"downloads": 637,
"gated": false,
"id": "mradermacher/Cyber-Prime-1.1-2.6B-GGUF",
"lastModified": "2026-09-26T01:03:44.000Z",
"library_name": "transformers",
"likes": 1,
"modelId": "mradermacher/Cyber-Prime-1.1-2.6B-GGUF",
"private": false,
"sha": "95576be097925d3cd711f1014e59679eca2836e1",
"siblings": [
{
"rfilename": ".gitattributes"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.IQ4_XS.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q2_K.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q3_K_L.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q3_K_M.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q3_K_S.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q4_K_M.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q4_K_S.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q5_K_M.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q5_K_S.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q6_K.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q8_0.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.f16.gguf"
},
{
"rfilename": "README.md"
}
],
"tags": [
"transformers",
"gguf",
"cybersecurity",
"cyberbench",
"threat-intelligence",
"named-entity-recognition",
"phishing-detection",
"http-anomaly-detection",
"lfm2",
"2.6b",
"en",
"dataset:jpmorganchase/CyberBench",
"dataset:tihanyin/CyberMetric",
"dataset:secbench-hf/SecBench",
"dataset:XuanwuAI/SecEval",
"base_model:Akahsizrr/Cyber-Prime-1.1-2.6B",
"base_model:quantized:Akahsizrr/Cyber-Prime-1.1-2.6B",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
]
} | — |
| Downloads downloads not compared | GGUF quantisations | 637receipt
What the source handed over{
"_id": "6ab484a9350763546e86ce3a",
"author": "mradermacher",
"cardData": {
"base_model": "Akahsizrr/Cyber-Prime-1.1-2.6B",
"datasets": [
"jpmorganchase/CyberBench",
"tihanyin/CyberMetric",
"secbench-hf/SecBench",
"XuanwuAI/SecEval"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "other",
"license_link": "LICENSE",
"license_name": "lfm1.0",
"mradermacher": {
"readme_rev": 1
},
"quantized_by": "mradermacher",
"tags": [
"cybersecurity",
"cyberbench",
"threat-intelligence",
"named-entity-recognition",
"phishing-detection",
"http-anomaly-detection",
"lfm2",
"2.6b"
]
},
"createdAt": "2026-09-24T02:02:17.000Z",
"downloads": 637,
"gated": false,
"id": "mradermacher/Cyber-Prime-1.1-2.6B-GGUF",
"lastModified": "2026-09-26T01:03:44.000Z",
"library_name": "transformers",
"likes": 1,
"modelId": "mradermacher/Cyber-Prime-1.1-2.6B-GGUF",
"private": false,
"sha": "95576be097925d3cd711f1014e59679eca2836e1",
"siblings": [
{
"rfilename": ".gitattributes"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.IQ4_XS.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q2_K.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q3_K_L.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q3_K_M.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q3_K_S.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q4_K_M.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q4_K_S.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q5_K_M.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q5_K_S.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q6_K.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q8_0.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.f16.gguf"
},
{
"rfilename": "README.md"
}
],
"tags": [
"transformers",
"gguf",
"cybersecurity",
"cyberbench",
"threat-intelligence",
"named-entity-recognition",
"phishing-detection",
"http-anomaly-detection",
"lfm2",
"2.6b",
"en",
"dataset:jpmorganchase/CyberBench",
"dataset:tihanyin/CyberMetric",
"dataset:secbench-hf/SecBench",
"dataset:XuanwuAI/SecEval",
"base_model:Akahsizrr/Cyber-Prime-1.1-2.6B",
"base_model:quantized:Akahsizrr/Cyber-Prime-1.1-2.6B",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
]
} | — |
| Downloads downloads not compared | Hugging Face models | 602receipt
This source has not kept a receipt for this claim yet. The next update that reads it will. | — |
| Downloads downloads not compared | 768receipt
What the source handed over{
"_asked": "Akahsizrr/Cyber-Prime-1.1-2.6B",
"_id": "6ab37c5c4d047e01ccd99b2a",
"author": "Akahsizrr",
"cardData": {
"base_model": "LiquidAI/LFM2-2.6B",
"datasets": [
"jpmorganchase/CyberBench",
"tihanyin/CyberMetric",
"secbench-hf/SecBench",
"XuanwuAI/SecEval"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "other",
"license_link": "LICENSE",
"license_name": "lfm1.0",
"pipeline_tag": "text-generation",
"tags": [
"cybersecurity",
"cyberbench",
"threat-intelligence",
"named-entity-recognition",
"phishing-detection",
"http-anomaly-detection",
"lfm2",
"2.6b"
]
},
"config": {
"architectures": [
"Lfm2ForCausalLM"
],
"chat_template_jinja": "{{- bos_token -}}\n{%- set preserve_thinking = preserve_thinking | default(false) -%}\n\n{%- macro format_arg_value(arg_value) -%}\n {%- if arg_value is string -%}\n {{- \"'\" + (arg_value | replace(\"\\\\\", \"\\\\\\\\\") | replace(\"'\", \"\\\\'\") | replace(\"\\n\", \"\\\\n\") | replace(\"\\r\", \"\\\\r\")) + \"'\" -}}\n {%- elif arg_value is mapping or arg_value is iterable -%}\n {{- arg_value | tojson -}}\n {%- else -%}\n {{- arg_value | string -}}\n {%- endif -%}\n{%- endmacro -%}\n\n{%- macro parse_content(content) -%}\n {%- if content is string -%}\n {{- content -}}\n {%- elif content is mapping -%}\n {{- content | tojson -}}\n {%- elif content is iterable -%}\n {%- set _ns = namespace(result=\"\") -%}\n {%- for item in content -%}\n {%- if item is string -%}\n {%- set _ns.result = _ns.result + item -%}\n {%- elif item is mapping and item.get(\"type\") == \"image\" -%}\n {%- set _ns.result = _ns.result + \"<image>\" -%}\n {%- elif item is mapping and item.get(\"type\") == \"text\" -%}\n {%- set _ns.result = _ns.result + ((item.get(\"text\") or \"\") | string) -%}\n {%- else -%}\n {%- set _ns.result = _ns.result + (item | tojson) -%}\n {%- endif -%}\n {%- endfor -%}\n {{- _ns.result -}}\n {%- endif -%}\n{%- endmacro -%}\n\n{%- macro render_tool_calls(tool_calls) -%}\n {%- set tool_calls_ns = namespace(tool_calls=[]) -%}\n {%- for tool_call in tool_calls -%}\n {%- set func = tool_call[\"function\"] if \"function\" in tool_call else tool_call -%}\n {%- set func_name = func[\"name\"] -%}\n {%- set func_args = func.get(\"arguments\") -%}\n {%- set args_ns = namespace(arg_strings=[]) -%}\n {%- if func_args is mapping -%}\n {%- for arg_name, arg_value in func_args.items() -%}\n {%- set args_ns.arg_strings = args_ns.arg_strings + [arg_name + \"=\" + format_arg_value(arg_value)] -%}\n {%- endfor -%}\n {%- elif func_args is string and (func_args | trim) not in [\"\", \"{}\", \"null\"] -%}\n {{- raise_exception(\"Tool call arguments must be a mapping, got a JSON-encoded string: parse arguments with json.loads() before applying the chat template\") -}}\n {%- endif -%}\n {%- set tool_calls_ns.tool_calls = tool_calls_ns.tool_calls + [func_name + \"(\" + (args_ns.arg_strings | join(\", \")) + \")\"] -%}\n {%- endfor -%}\n {{- \"<|tool_call_start|>[\" + (tool_calls_ns.tool_calls | join(\", \")) + \"]<|tool_call_end|>\" -}}\n{%- endmacro -%}\n\n{%- set ns = namespace(system_prompt=\"\", last_user_index=-1) -%}\n{%- if messages and messages[0][\"role\"] == \"system\" -%}\n {%- if messages[0].get(\"content\") -%}\n {%- set ns.system_prompt = parse_content(messages[0][\"content\"]) -%}\n {%- endif -%}\n {%- set messages = messages[1:] -%}\n{%- endif -%}\n{%- if tools -%}\n {%- set ns.system_prompt = ns.system_prompt + (\"\\n\" if ns.system_prompt else \"\") + \"List of tools: [\" -%}\n {%- for tool in tools -%}\n {%- if tool is not string -%}\n {%- set tool = tool | tojson -%}\n {%- endif -%}\n {%- set ns.system_prompt = ns.system_prompt + tool -%}\n {%- if not loop.last -%}\n {%- set ns.system_prompt = ns.system_prompt + \", \" -%}\n {%- endif -%}\n {%- endfor -%}\n {%- set ns.system_prompt = ns.system_prompt + \"]\" -%}\n{%- endif -%}\n{%- if ns.system_prompt -%}\n {{- \"<|im_start|>system\\n\" + ns.system_prompt + \"<|im_end|>\\n\" -}}\n{%- endif -%}\n{%- for message in messages -%}\n {%- if message[\"role\"] == \"user\" -%}\n {%- set ns.last_user_index = loop.index0 -%}\n {%- endif -%}\n{%- endfor -%}\n{%- for message in messages -%}\n {{- \"<|im_start|>\" + message.role + \"\\n\" -}}\n {%- if message.role == \"assistant\" -%}\n {%- generation -%}\n {%- set keep_thinking = preserve_thinking or loop.index0 > ns.last_user_index -%}\n {%- set thinking = message.thinking or message.reasoning or message.reasoning_content -%}\n {%- set thinking = thinking if thinking is string else \"\" -%}\n {%- if thinking and keep_thinking -%}\n {{- \"<think>\" + thinking + \"</think>\" -}}\n {%- endif -%}\n {%- set _cfm_tag = \"CONTINUE_FINAL_MESSAGE_TAG \" -%}\n {%- set _has_cfm = false -%}\n {%- set content = \"\" -%}\n {%- if message.get(\"content\") -%}\n {%- set content = parse_content(message.content) -%}\n {%- endif -%}\n {%- if not keep_thinking and \"</think>\" in content -%}\n {%- set content = content.split(\"</think>\")[-1] | trim -%}\n {%- endif -%}\n {%- if content.endswith(_cfm_tag) -%}\n {%- set _has_cfm = true -%}\n {%- set _trunc_len = (content | length) - (_cfm_tag | length) -%}\n {%- set content = content[:_trunc_len] -%}\n {%- endif -%}\n {{- content -}}\n {%- if message.tool_calls -%}\n {{- render_tool_calls(message.tool_calls) -}}\n {%- endif -%}\n {%- if _has_cfm -%}\n {{- _cfm_tag -}}\n {%- endif -%}\n {{- \"<|im_end|>\\n\" -}}\n {%- endgeneration -%}\n {%- else %}\n {%- if message.get(\"content\") -%}\n {{- parse_content(message[\"content\"]) -}}\n {%- endif -%}\n {{- \"<|im_end|>\\n\" -}}\n {%- endif %}\n{%- endfor -%}\n{%- if add_generation_prompt -%}\n {{- \"<|im_start|>assistant\\n<think>\" -}}\n{%- endif -%}\n",
"model_type": "lfm2",
"tokenizer_config": {
"bos_token": "<|startoftext|>",
"eos_token": "<|im_end|>",
"pad_token": "<|pad|>",
"use_default_system_prompt": false
}
},
"createdAt": "2026-09-23T07:14:36.000Z",
"disabled": false,
"downloads": 768,
"gated": false,
"id": "Akahsizrr/Cyber-Prime-1.1-2.6B",
"lastModified": "2026-09-25T20:39:43.000Z",
"library_name": "transformers",
"likes": 10,
"model-index": null,
"modelId": "Akahsizrr/Cyber-Prime-1.1-2.6B",
"pipeline_tag": "text-generation",
"private": false,
"safetensors": {
"parameters": {
"BF16": 2697198592
},
"total": 2697198592
},
"sha": "b7ff7d9a55a76c1869f539add9a02135144c6d47",
"siblings": [
{
"rfilename": ".gitattributes"
},
{
"rfilename": "LICENSE"
},
{
"rfilename": "README.md"
},
{
"rfilename": "chat_template.jinja"
},
{
"rfilename": "config.json"
},
{
"rfilename": "cyberprime-1.1-benchmark.png"
},
{
"rfilename": "generation_config.json"
},
{
"rfilename": "model-00001-of-00002.safetensors"
},
{
"rfilename": "model-00002-of-00002.safetensors"
},
{
"rfilename": "model.safetensors.index.json"
},
{
"rfilename": "special_tokens_map.json"
},
{
"rfilename": "tokenizer.json"
},
{
"rfilename": "tokenizer_config.json"
}
],
"spaces": [],
"tags": [
"transformers",
"safetensors",
"lfm2",
"text-generation",
"cybersecurity",
"cyberbench",
"threat-intelligence",
"named-entity-recognition",
"phishing-detection",
"http-anomaly-detection",
"2.6b",
"conversational",
"en",
"dataset:jpmorganchase/CyberBench",
"dataset:tihanyin/CyberMetric",
"dataset:secbench-hf/SecBench",
"dataset:XuanwuAI/SecEval",
"base_model:LiquidAI/LFM2-2.6B",
"base_model:finetune:LiquidAI/LFM2-2.6B",
"license:other",
"endpoints_compatible",
"region:us"
],
"transformersInfo": {
"auto_model": "AutoModelForCausalLM",
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
},
"usedStorage": 10807165025,
"widgetData": [
{
"text": "Hi, what can you help me with?"
},
{
"text": "What is 84 * 3 / 2?"
},
{
"text": "Tell me an interesting fact about the universe!"
},
{
"text": "Explain quantum computing in simple terms."
}
]
} | — | |
| Gated gated | Hugging Face models | falsereceipt
This source has not kept a receipt for this claim yet. The next update that reads it will. | — |
| Licence licence | GGUF quantisations | otherreceipt
What the source handed over{
"_id": "6ab484a9350763546e86ce3a",
"author": "mradermacher",
"cardData": {
"base_model": "Akahsizrr/Cyber-Prime-1.1-2.6B",
"datasets": [
"jpmorganchase/CyberBench",
"tihanyin/CyberMetric",
"secbench-hf/SecBench",
"XuanwuAI/SecEval"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "other",
"license_link": "LICENSE",
"license_name": "lfm1.0",
"mradermacher": {
"readme_rev": 1
},
"quantized_by": "mradermacher",
"tags": [
"cybersecurity",
"cyberbench",
"threat-intelligence",
"named-entity-recognition",
"phishing-detection",
"http-anomaly-detection",
"lfm2",
"2.6b"
]
},
"createdAt": "2026-09-24T02:02:17.000Z",
"downloads": 637,
"gated": false,
"id": "mradermacher/Cyber-Prime-1.1-2.6B-GGUF",
"lastModified": "2026-09-26T01:03:44.000Z",
"library_name": "transformers",
"likes": 1,
"modelId": "mradermacher/Cyber-Prime-1.1-2.6B-GGUF",
"private": false,
"sha": "95576be097925d3cd711f1014e59679eca2836e1",
"siblings": [
{
"rfilename": ".gitattributes"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.IQ4_XS.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q2_K.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q3_K_L.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q3_K_M.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q3_K_S.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q4_K_M.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q4_K_S.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q5_K_M.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q5_K_S.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q6_K.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q8_0.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.f16.gguf"
},
{
"rfilename": "README.md"
}
],
"tags": [
"transformers",
"gguf",
"cybersecurity",
"cyberbench",
"threat-intelligence",
"named-entity-recognition",
"phishing-detection",
"http-anomaly-detection",
"lfm2",
"2.6b",
"en",
"dataset:jpmorganchase/CyberBench",
"dataset:tihanyin/CyberMetric",
"dataset:secbench-hf/SecBench",
"dataset:XuanwuAI/SecEval",
"base_model:Akahsizrr/Cyber-Prime-1.1-2.6B",
"base_model:quantized:Akahsizrr/Cyber-Prime-1.1-2.6B",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
]
} | — |
| Licence licence | Hugging Face models | otherreceipt
This source has not kept a receipt for this claim yet. The next update that reads it will. | — |
| Likes likes not compared | GGUF quantisations | 1receipt
What the source handed over{
"_id": "6ab484a9350763546e86ce3a",
"author": "mradermacher",
"cardData": {
"base_model": "Akahsizrr/Cyber-Prime-1.1-2.6B",
"datasets": [
"jpmorganchase/CyberBench",
"tihanyin/CyberMetric",
"secbench-hf/SecBench",
"XuanwuAI/SecEval"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "other",
"license_link": "LICENSE",
"license_name": "lfm1.0",
"mradermacher": {
"readme_rev": 1
},
"quantized_by": "mradermacher",
"tags": [
"cybersecurity",
"cyberbench",
"threat-intelligence",
"named-entity-recognition",
"phishing-detection",
"http-anomaly-detection",
"lfm2",
"2.6b"
]
},
"createdAt": "2026-09-24T02:02:17.000Z",
"downloads": 637,
"gated": false,
"id": "mradermacher/Cyber-Prime-1.1-2.6B-GGUF",
"lastModified": "2026-09-26T01:03:44.000Z",
"library_name": "transformers",
"likes": 1,
"modelId": "mradermacher/Cyber-Prime-1.1-2.6B-GGUF",
"private": false,
"sha": "95576be097925d3cd711f1014e59679eca2836e1",
"siblings": [
{
"rfilename": ".gitattributes"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.IQ4_XS.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q2_K.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q3_K_L.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q3_K_M.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q3_K_S.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q4_K_M.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q4_K_S.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q5_K_M.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q5_K_S.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q6_K.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.Q8_0.gguf"
},
{
"rfilename": "Cyber-Prime-1.1-2.6B.f16.gguf"
},
{
"rfilename": "README.md"
}
],
"tags": [
"transformers",
"gguf",
"cybersecurity",
"cyberbench",
"threat-intelligence",
"named-entity-recognition",
"phishing-detection",
"http-anomaly-detection",
"lfm2",
"2.6b",
"en",
"dataset:jpmorganchase/CyberBench",
"dataset:tihanyin/CyberMetric",
"dataset:secbench-hf/SecBench",
"dataset:XuanwuAI/SecEval",
"base_model:Akahsizrr/Cyber-Prime-1.1-2.6B",
"base_model:quantized:Akahsizrr/Cyber-Prime-1.1-2.6B",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
]
} | — |
| Likes likes not compared | Hugging Face models | 10receipt
What the source handed over{
"_asked": "Akahsizrr/Cyber-Prime-1.1-2.6B",
"_id": "6ab37c5c4d047e01ccd99b2a",
"author": "Akahsizrr",
"cardData": {
"base_model": "LiquidAI/LFM2-2.6B",
"datasets": [
"jpmorganchase/CyberBench",
"tihanyin/CyberMetric",
"secbench-hf/SecBench",
"XuanwuAI/SecEval"
],
"language": [
"en"
],
"library_name": "transformers",
"license": "other",
"license_link": "LICENSE",
"license_name": "lfm1.0",
"pipeline_tag": "text-generation",
"tags": [
"cybersecurity",
"cyberbench",
"threat-intelligence",
"named-entity-recognition",
"phishing-detection",
"http-anomaly-detection",
"lfm2",
"2.6b"
]
},
"config": {
"architectures": [
"Lfm2ForCausalLM"
],
"chat_template_jinja": "{{- bos_token -}}\n{%- set preserve_thinking = preserve_thinking | default(false) -%}\n\n{%- macro format_arg_value(arg_value) -%}\n {%- if arg_value is string -%}\n {{- \"'\" + (arg_value | replace(\"\\\\\", \"\\\\\\\\\") | replace(\"'\", \"\\\\'\") | replace(\"\\n\", \"\\\\n\") | replace(\"\\r\", \"\\\\r\")) + \"'\" -}}\n {%- elif arg_value is mapping or arg_value is iterable -%}\n {{- arg_value | tojson -}}\n {%- else -%}\n {{- arg_value | string -}}\n {%- endif -%}\n{%- endmacro -%}\n\n{%- macro parse_content(content) -%}\n {%- if content is string -%}\n {{- content -}}\n {%- elif content is mapping -%}\n {{- content | tojson -}}\n {%- elif content is iterable -%}\n {%- set _ns = namespace(result=\"\") -%}\n {%- for item in content -%}\n {%- if item is string -%}\n {%- set _ns.result = _ns.result + item -%}\n {%- elif item is mapping and item.get(\"type\") == \"image\" -%}\n {%- set _ns.result = _ns.result + \"<image>\" -%}\n {%- elif item is mapping and item.get(\"type\") == \"text\" -%}\n {%- set _ns.result = _ns.result + ((item.get(\"text\") or \"\") | string) -%}\n {%- else -%}\n {%- set _ns.result = _ns.result + (item | tojson) -%}\n {%- endif -%}\n {%- endfor -%}\n {{- _ns.result -}}\n {%- endif -%}\n{%- endmacro -%}\n\n{%- macro render_tool_calls(tool_calls) -%}\n {%- set tool_calls_ns = namespace(tool_calls=[]) -%}\n {%- for tool_call in tool_calls -%}\n {%- set func = tool_call[\"function\"] if \"function\" in tool_call else tool_call -%}\n {%- set func_name = func[\"name\"] -%}\n {%- set func_args = func.get(\"arguments\") -%}\n {%- set args_ns = namespace(arg_strings=[]) -%}\n {%- if func_args is mapping -%}\n {%- for arg_name, arg_value in func_args.items() -%}\n {%- set args_ns.arg_strings = args_ns.arg_strings + [arg_name + \"=\" + format_arg_value(arg_value)] -%}\n {%- endfor -%}\n {%- elif func_args is string and (func_args | trim) not in [\"\", \"{}\", \"null\"] -%}\n {{- raise_exception(\"Tool call arguments must be a mapping, got a JSON-encoded string: parse arguments with json.loads() before applying the chat template\") -}}\n {%- endif -%}\n {%- set tool_calls_ns.tool_calls = tool_calls_ns.tool_calls + [func_name + \"(\" + (args_ns.arg_strings | join(\", \")) + \")\"] -%}\n {%- endfor -%}\n {{- \"<|tool_call_start|>[\" + (tool_calls_ns.tool_calls | join(\", \")) + \"]<|tool_call_end|>\" -}}\n{%- endmacro -%}\n\n{%- set ns = namespace(system_prompt=\"\", last_user_index=-1) -%}\n{%- if messages and messages[0][\"role\"] == \"system\" -%}\n {%- if messages[0].get(\"content\") -%}\n {%- set ns.system_prompt = parse_content(messages[0][\"content\"]) -%}\n {%- endif -%}\n {%- set messages = messages[1:] -%}\n{%- endif -%}\n{%- if tools -%}\n {%- set ns.system_prompt = ns.system_prompt + (\"\\n\" if ns.system_prompt else \"\") + \"List of tools: [\" -%}\n {%- for tool in tools -%}\n {%- if tool is not string -%}\n {%- set tool = tool | tojson -%}\n {%- endif -%}\n {%- set ns.system_prompt = ns.system_prompt + tool -%}\n {%- if not loop.last -%}\n {%- set ns.system_prompt = ns.system_prompt + \", \" -%}\n {%- endif -%}\n {%- endfor -%}\n {%- set ns.system_prompt = ns.system_prompt + \"]\" -%}\n{%- endif -%}\n{%- if ns.system_prompt -%}\n {{- \"<|im_start|>system\\n\" + ns.system_prompt + \"<|im_end|>\\n\" -}}\n{%- endif -%}\n{%- for message in messages -%}\n {%- if message[\"role\"] == \"user\" -%}\n {%- set ns.last_user_index = loop.index0 -%}\n {%- endif -%}\n{%- endfor -%}\n{%- for message in messages -%}\n {{- \"<|im_start|>\" + message.role + \"\\n\" -}}\n {%- if message.role == \"assistant\" -%}\n {%- generation -%}\n {%- set keep_thinking = preserve_thinking or loop.index0 > ns.last_user_index -%}\n {%- set thinking = message.thinking or message.reasoning or message.reasoning_content -%}\n {%- set thinking = thinking if thinking is string else \"\" -%}\n {%- if thinking and keep_thinking -%}\n {{- \"<think>\" + thinking + \"</think>\" -}}\n {%- endif -%}\n {%- set _cfm_tag = \"CONTINUE_FINAL_MESSAGE_TAG \" -%}\n {%- set _has_cfm = false -%}\n {%- set content = \"\" -%}\n {%- if message.get(\"content\") -%}\n {%- set content = parse_content(message.content) -%}\n {%- endif -%}\n {%- if not keep_thinking and \"</think>\" in content -%}\n {%- set content = content.split(\"</think>\")[-1] | trim -%}\n {%- endif -%}\n {%- if content.endswith(_cfm_tag) -%}\n {%- set _has_cfm = true -%}\n {%- set _trunc_len = (content | length) - (_cfm_tag | length) -%}\n {%- set content = content[:_trunc_len] -%}\n {%- endif -%}\n {{- content -}}\n {%- if message.tool_calls -%}\n {{- render_tool_calls(message.tool_calls) -}}\n {%- endif -%}\n {%- if _has_cfm -%}\n {{- _cfm_tag -}}\n {%- endif -%}\n {{- \"<|im_end|>\\n\" -}}\n {%- endgeneration -%}\n {%- else %}\n {%- if message.get(\"content\") -%}\n {{- parse_content(message[\"content\"]) -}}\n {%- endif -%}\n {{- \"<|im_end|>\\n\" -}}\n {%- endif %}\n{%- endfor -%}\n{%- if add_generation_prompt -%}\n {{- \"<|im_start|>assistant\\n<think>\" -}}\n{%- endif -%}\n",
"model_type": "lfm2",
"tokenizer_config": {
"bos_token": "<|startoftext|>",
"eos_token": "<|im_end|>",
"pad_token": "<|pad|>",
"use_default_system_prompt": false
}
},
"createdAt": "2026-09-23T07:14:36.000Z",
"disabled": false,
"downloads": 768,
"gated": false,
"id": "Akahsizrr/Cyber-Prime-1.1-2.6B",
"lastModified": "2026-09-25T20:39:43.000Z",
"library_name": "transformers",
"likes": 10,
"model-index": null,
"modelId": "Akahsizrr/Cyber-Prime-1.1-2.6B",
"pipeline_tag": "text-generation",
"private": false,
"safetensors": {
"parameters": {
"BF16": 2697198592
},
"total": 2697198592
},
"sha": "b7ff7d9a55a76c1869f539add9a02135144c6d47",
"siblings": [
{
"rfilename": ".gitattributes"
},
{
"rfilename": "LICENSE"
},
{
"rfilename": "README.md"
},
{
"rfilename": "chat_template.jinja"
},
{
"rfilename": "config.json"
},
{
"rfilename": "cyberprime-1.1-benchmark.png"
},
{
"rfilename": "generation_config.json"
},
{
"rfilename": "model-00001-of-00002.safetensors"
},
{
"rfilename": "model-00002-of-00002.safetensors"
},
{
"rfilename": "model.safetensors.index.json"
},
{
"rfilename": "special_tokens_map.json"
},
{
"rfilename": "tokenizer.json"
},
{
"rfilename": "tokenizer_config.json"
}
],
"spaces": [],
"tags": [
"transformers",
"safetensors",
"lfm2",
"text-generation",
"cybersecurity",
"cyberbench",
"threat-intelligence",
"named-entity-recognition",
"phishing-detection",
"http-anomaly-detection",
"2.6b",
"conversational",
"en",
"dataset:jpmorganchase/CyberBench",
"dataset:tihanyin/CyberMetric",
"dataset:secbench-hf/SecBench",
"dataset:XuanwuAI/SecEval",
"base_model:LiquidAI/LFM2-2.6B",
"base_model:finetune:LiquidAI/LFM2-2.6B",
"license:other",
"endpoints_compatible",
"region:us"
],
"transformersInfo": {
"auto_model": "AutoModelForCausalLM",
"pipeline_tag": "text-generation",
"processor": "AutoTokenizer"
},
"usedStorage": 10807165025,
"widgetData": [
{
"text": "Hi, what can you help me with?"
},
{
"text": "What is 84 * 3 / 2?"
},
{
"text": "Tell me an interesting fact about the universe!"
},
{
"text": "Explain quantum computing in simple terms."
}
]
} | — |
| Likes likes not compared | 3receipt
This source has not kept a receipt for this claim yet. The next update that reads it will. | — | |
| Task task | Hugging Face models | text-generationreceipt
This source has not kept a receipt for this claim yet. The next update that reads it will. | — |
model
| Akahsizrr/Cyber-Prime-1.1-2.6B zetlyn/models-hf · 2026-09-23 | author Akahsizrr downloads 602 gated false licence other likes 3 task text-generation | source |
| Akahsizrr/Cyber-Prime-1.1-2.6B zetlyn/models-hf · 2026-09-23 | author Akahsizrr downloads 768 gated false licence other likes 10 task text-generation | source |
quantisation
| mradermacher/Cyber-Prime-1.1-2.6B-GGUF zetlyn/models-gguf · 2026-09-24 | author mradermacher base Akahsizrr/Cyber-Prime-1.1-2.6B downloads 637 licence other likes 1 | source |