From fc6fef9d1020cd22e82ae48e738def3042a3e9a9 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Mon, 20 Jul 2026 21:09:10 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: sallani/ISO42001-Qwen2.5-0.5B-Edge Source: Original Platform --- .gitattributes | 37 ++++ README.md | 214 +++++++++++++++++++++++ chat_template.jinja | 54 ++++++ config.json | 30 ++++ generation_config.json | 14 ++ iso42001-qwen2.5-0.5b-f16.gguf | 3 + model.safetensors | 3 + model.safetensors.index.json | 298 +++++++++++++++++++++++++++++++++ tokenizer.json | 3 + tokenizer_config.json | 31 ++++ 10 files changed, 687 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 chat_template.jinja create mode 100644 config.json create mode 100644 generation_config.json create mode 100644 iso42001-qwen2.5-0.5b-f16.gguf create mode 100644 model.safetensors create mode 100644 model.safetensors.index.json create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..63492a7 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,37 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text +iso42001-qwen2.5-0.5b-f16.gguf filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..38cf1b5 --- /dev/null +++ b/README.md @@ -0,0 +1,214 @@ +--- +language: + - fr + - en +license: apache-2.0 +base_model: Qwen/Qwen2.5-0.5B-Instruct +tags: + - iso42001 + - ai-governance + - ai-management-system + - aims + - eu-ai-act + - grc + - compliance + - edge + - qlora + - mlx + - fine-tuned + - on-premise + - sovereign-ai +pipeline_tag: text-generation +library_name: transformers +--- + +# ISO42001-Qwen2.5-0.5B-Edge + +

+ + + + + +

+ +> **Specialized SLM for ISO/IEC 42001:2023 — AI Management System.** +> Fine-tuned on Qwen2.5-0.5B-Instruct. Runs fully on-premise, offline, with no external dependencies. + +--- + +## Overview + +| | | +|---|---| +| **Base model** | `Qwen/Qwen2.5-0.5B-Instruct` (Apache 2.0) | +| **Architecture** | Qwen2 — 24 layers · 896 hidden dim · 14 heads · 0.5B parameters | +| **Fine-tuning** | MLX LoRA (Apple Silicon) · QLoRA 4-bit NF4 (GPU) | +| **Domain** | ISO/IEC 42001:2023 · EU AI Act · GDPR × AI · AI Governance | +| **Languages** | French · English | +| **Deployment** | On-premise · Offline · Ollama · llama.cpp · LM Studio | + +--- + +## What is this model for? + +ISO/IEC 42001:2023 is the first international standard for **AI Management Systems (AIMS)**. It provides organizations that develop, deploy, or use AI with a governance framework to demonstrate responsible and ethical AI use — increasingly required in the context of the EU AI Act. + +This model gives CISOs, DPOs, CAIOs, and GRC consultants precise, clause-referenced answers on: + +- **Clauses 4–10** — context, leadership, planning, support, operations, performance evaluation, improvement +- **Annex A** — all controls: A.2 policies · A.6 AI system operation · A.7 transparency · A.8 data governance · A.10 supply chain +- **EU AI Act × ISO 42001 mapping** — 4 risk levels, obligations per category +- **ISO 27001 × ISO 42001 × GDPR integration** — unified governance approach +- **Practical topics** — impact assessment, model cards, SoA, AI system register, privacy risk + +--- + +## Example queries + +``` +What is the scope of ISO/IEC 42001:2023? +How is Annex A of ISO 42001 structured? +How to conduct an AI Impact Assessment per control A.6.1? +What are the human oversight requirements under ISO 42001 (A.6.2)? +How does ISO 42001 map to EU AI Act Article 9? +What data governance controls does ISO 42001 require for AI systems (A.8)? +Qu'est-ce qu'un Statement of Applicability dans ISO 42001 ? +Comment certifier un AIMS ISO 42001 ? Quelles sont les étapes ? +Quelle est la différence entre ISO 27001 et ISO 42001 ? +Comment créer un registre des systèmes d'IA conforme à ISO 42001 ? +``` + +--- + +## Inference + +### HuggingFace Transformers + +```python +from transformers import AutoModelForCausalLM, AutoTokenizer +import torch + +model_id = "sallani/ISO42001-Qwen2.5-0.5B-Edge" + +tokenizer = AutoTokenizer.from_pretrained(model_id) +model = AutoModelForCausalLM.from_pretrained( + model_id, + torch_dtype=torch.bfloat16, + device_map="auto", +) + +messages = [ + { + "role": "system", + "content": ( + "You are an expert assistant in AI governance and management systems, " + "specializing in ISO/IEC 42001:2023 (AI Management System), the EU AI Act, " + "and GDPR applied to AI. Your answers are precise, clause-referenced, " + "and tailored to compliance professionals (CISOs, DPOs, CAIOs, GRC consultants)." + ) + }, + { + "role": "user", + "content": "What are the key controls in ISO 42001 Annex A for AI system operations?" + } +] + +text = tokenizer.apply_chat_template( + messages, tokenize=False, add_generation_prompt=True +) +inputs = tokenizer(text, return_tensors="pt").to(model.device) + +with torch.no_grad(): + outputs = model.generate( + **inputs, + max_new_tokens=512, + temperature=0.1, + top_p=0.9, + repetition_penalty=1.1, + do_sample=True, + ) + +print(tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)) +``` + +### Ollama (GGUF Q4_K_M) + +```bash +ollama create iso42001-edge -f Modelfile +ollama run iso42001-edge "How to conduct an AI Impact Assessment per ISO 42001 A.6.1?" +``` + +### llama.cpp + +```bash +./llama-cli \ + -m iso42001-qwen2.5-0.5b-q4_k_m.gguf \ + --system-prompt "You are an ISO/IEC 42001:2023 AI governance expert." \ + -p "What is the scope of ISO 42001?" \ + -n 512 --temp 0.1 +``` + +--- + +## Training details + +### Dataset + +47 instruction-following Q&A pairs (FR/EN) covering the full standard: + +| File | Examples | Split | +|------|----------|-------| +| `iso42001_train.jsonl` | 37 | Training | +| `iso42001_test.jsonl` | 10 | Evaluation (out-of-distribution) | + +**Thematic coverage:** + +- Clauses 4–6: Context · Leadership · Planning · AI Impact Assessment · Risk assessment +- Clauses 7–8: Support · Operations · AI lifecycle · Data governance (A.8) · Human oversight (A.6.2) +- Clauses 9–10: Performance evaluation · Internal audit · Continual improvement +- EU AI Act × ISO 42001: full 4-level risk mapping +- ISO 27001 × ISO 42001 × GDPR integration +- Practical topics: SoA · AI system register · model card · certification steps + +### Hyperparameters + +| Parameter | Value | +|-----------|-------| +| Technique | MLX LoRA (Apple M-series) | +| LoRA rank | 8 | +| LoRA layers | 4 | +| Iterations | 100 | +| Batch size | 8 | +| Learning rate | 5e-5 | +| Max seq length | 1024 | +| Optimizer | Adam | + +--- + +## Offline deployment + +This model is designed to run **fully locally** with no network calls at inference time. + +- ✅ No data sent to external cloud services +- ✅ CPU-compatible via GGUF Q4_K_M (8 GB RAM minimum) +- ✅ Apple Silicon optimized via MLX +- ✅ Compatible with Ollama · llama.cpp · LM Studio · Jan +- ✅ Apache 2.0 license — commercial use permitted +- ✅ Fully reproducible fine-tuning from source + +--- + +## Limitations + +- Compact dataset (47 pairs) — suited for specialized Q&A and evaluation, not production-critical use without further enrichment +- 0.5B model — limited on complex multi-step reasoning chains +- Does not replace a certified ISO 42001 audit conducted by a qualified professional +- Outputs should be reviewed by a subject matter expert before any regulatory decision + +--- + +## License + +This model is released under **Apache 2.0**. +Base model: [Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) — Apache 2.0, Alibaba Cloud. diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000..bdf7919 --- /dev/null +++ b/chat_template.jinja @@ -0,0 +1,54 @@ +{%- if tools %} + {{- '<|im_start|>system\n' }} + {%- if messages[0]['role'] == 'system' %} + {{- messages[0]['content'] }} + {%- else %} + {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }} + {%- endif %} + {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within XML tags:\n" }} + {%- for tool in tools %} + {{- "\n" }} + {{- tool | tojson }} + {%- endfor %} + {{- "\n\n\nFor each function call, return a json object with function name and arguments within XML tags:\n\n{\"name\": , \"arguments\": }\n<|im_end|>\n" }} +{%- else %} + {%- if messages[0]['role'] == 'system' %} + {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }} + {%- else %} + {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }} + {%- endif %} +{%- endif %} +{%- for message in messages %} + {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %} + {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }} + {%- elif message.role == "assistant" %} + {{- '<|im_start|>' + message.role }} + {%- if message.content %} + {{- '\n' + message.content }} + {%- endif %} + {%- for tool_call in message.tool_calls %} + {%- if tool_call.function is defined %} + {%- set tool_call = tool_call.function %} + {%- endif %} + {{- '\n\n{"name": "' }} + {{- tool_call.name }} + {{- '", "arguments": ' }} + {{- tool_call.arguments | tojson }} + {{- '}\n' }} + {%- endfor %} + {{- '<|im_end|>\n' }} + {%- elif message.role == "tool" %} + {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %} + {{- '<|im_start|>user' }} + {%- endif %} + {{- '\n\n' }} + {{- 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