From e5701aed8a781bbf77abc4a7410645f7c399d3e6 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Sat, 27 Jun 2026 19:58:16 +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: GSMS-B/Indian-Legal-Qwen2.5-3B Source: Original Platform --- .gitattributes | 36 +++ README.md | 172 ++++++++++++ chat_template.jinja | 54 ++++ config.json | 70 +++++ generation_config.json | 14 + model-00001-of-00002.safetensors | 3 + model-00002-of-00002.safetensors | 3 + model.safetensors.index.json | 441 +++++++++++++++++++++++++++++++ tokenizer.json | 3 + tokenizer_config.json | 202 ++++++++++++++ 10 files changed, 998 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 model-00001-of-00002.safetensors create mode 100644 model-00002-of-00002.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..52373fe --- /dev/null +++ b/.gitattributes @@ -0,0 +1,36 @@ +*.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 diff --git a/README.md b/README.md new file mode 100644 index 0000000..65f5a61 --- /dev/null +++ b/README.md @@ -0,0 +1,172 @@ +--- +language: +- en +license: apache-2.0 +base_model: unsloth/Qwen2.5-1.5B-Instruct +tags: +- legal +- indian-law +- BNS +- BNSS +- BSA +- criminal-law +- qwen +- qwen2.5 +- qlora +- unsloth +- domain-adaptation +- instruction-tuning +- question-answering +- law +- india +datasets: +- GSMS-B/Indian-Legal-QA-BNS-BNSS-BSA +pipeline_tag: text-generation +--- + +# โš–๏ธ๐Ÿ‰ Indian Legal Qwen 2.5 โ€” 3B + +

+ Base Model + Type + Domain + Method + Acts + License +

+ +> ๐ŸŸข **This is the fully merged model** โ€” ready for out-of-the-box inference with no extra setup. For lightweight adapter loading see the [Adapter](https://huggingface.co/GSMS-B/Indian-Legal-Qwen2.5-3B-Adapter) ยท For CPU/Ollama usage see the [GGUF](https://huggingface.co/GSMS-B/Indian-Legal-Qwen2.5-3B-GGUF). + +--- + +## ๐Ÿ“– Model Description + +**Indian Legal Qwen 2.5 โ€” 3B** is a domain-adapted version of [`unsloth/Qwen2.5-3B-Instruct-bnb-4bit`](https://huggingface.co/unsloth/Qwen2.5-3B-Instruct-bnb-4bit), fine-tuned using QLoRA on a structured question-answer dataset covering all **1,059 sections** of India's three landmark 2023 criminal justice reform acts: + +| Act | Full Name | Replaces | Sections | +|---|---|---|---| +| ๐Ÿ“• **BNS 2023** | Bharatiya Nyaya Sanhita | IPC 1860 | 358 | +| ๐Ÿ“— **BNSS 2023** | Bharatiya Nagarik Suraksha Sanhita | CrPC 1973 | 531 | +| ๐Ÿ“˜ **BSA 2023** | Bharatiya Sakshya Adhiniyam | Indian Evidence Act 1872 | 170 | + +Trained on **6,354 instruction-format QA pairs** โ€” 6 question types per section covering definitions, scenarios, legal elements, exceptions, and consequences โ€” giving it broad, structured coverage of India's reformed criminal law framework. + +--- + +## ๐Ÿ”— Model Family โ€” Qwen 2.5 3B + +| Variant | Repo | Best For | +|---|---|---| +| ๐ŸŸข **Merged (this repo)** | `GSMS-B/Indian-Legal-Qwen2.5-3B` | Out-of-the-box inference, Gradio / API deployment | +| ๐Ÿ”ต **LoRA Adapter** | [GSMS-B/Indian-Legal-Qwen2.5-3B-Adapter](https://huggingface.co/GSMS-B/Indian-Legal-Qwen2.5-3B-Adapter) | Lightweight loading on top of base model | +| ๐ŸŸก **GGUF (Quantized)** | [GSMS-B/Indian-Legal-Qwen2.5-3B-GGUF](https://huggingface.co/GSMS-B/Indian-Legal-Qwen2.5-3B-GGUF) | CPU inference via Ollama / llama.cpp | + +--- + +## ๐Ÿš€ Quick Start + +```python +from transformers import AutoModelForCausalLM, AutoTokenizer +import torch + +model_id = "GSMS-B/Indian-Legal-Qwen2.5-3B" +tokenizer = AutoTokenizer.from_pretrained(model_id) +model = AutoModelForCausalLM.from_pretrained( + model_id, + torch_dtype=torch.float16, + device_map="auto" +) + +SYSTEM = "You are an expert legal assistant specializing in Indian criminal law โ€” BNS, BNSS, and BSA 2023." + +def ask(question): + messages = [ + {"role": "system", "content": SYSTEM}, + {"role": "user", "content": question} + ] + 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(): + out = model.generate(**inputs, max_new_tokens=300, temperature=0.1, + do_sample=True, pad_token_id=tokenizer.eos_token_id) + return tokenizer.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True) + +print(ask("What is a Zero FIR under BNSS 2023?")) +``` + +### ๐Ÿ’ป Run locally with Ollama (GGUF) +```bash +ollama run hf.co/GSMS-B/Indian-Legal-Qwen2.5-3B-GGUF +``` + +--- + +## ๐ŸŽฏ Recommended Use Cases + +> โš ๏ธ **Important Note:** This model has been domain-adapted on structured QA data and works best as a **component in a larger pipeline** rather than a standalone answer engine. Direct usage without retrieval context may produce incomplete or imprecise answers on complex legal queries. + +### โœ… Where this model excels + +| Use Case | ๐Ÿ’ก How to Use | +|---|---| +| ๐Ÿ” **RAG Pipeline** | Pair with a BM25 or vector retriever over BNS/BNSS/BSA texts; feed retrieved sections as context for grounded, citation-backed answers | +| ๐Ÿค– **Legal Chatbot Backend** | Use as the generation backbone of a legal assistant app with a ChromaDB / FAISS document store | +| ๐Ÿ“š **Legal Education Tool** | Build interactive Q&A apps for law students and practitioners learning the 2023 criminal justice reforms | +| ๐Ÿ”Ž **Section Lookup Assistant** | Combine with a section index to surface the exact BNS / BNSS / BSA provision relevant to a given situation | +| ๐Ÿงช **Further Fine-tuning** | Use as a starting point for more specialised adaptation (e.g., only BNSS procedure, only BSA evidence rules) | +| ๐Ÿ“ **Structured Legal Summarization** | Summarize individual sections when the section text is supplied as input context | +| ๐Ÿ›๏ธ **Legal NLP Research** | Benchmark Indian criminal law understanding across model families (Qwen vs Llama) | +| โš–๏ธ **Comparative Law Analysis** | Highlight differences between old acts (IPC/CrPC/IEA) and their 2023 replacements | + +### โŒ Not recommended for +- Standalone legal advice without a retrieval component +- High-stakes legal decisions without qualified human review +- Jurisdictions or acts outside BNS / BNSS / BSA 2023 + +--- + +## ๐Ÿ‹๏ธ Training Details + +| Property | Value | +|---|---| +| ๐Ÿค– Base model | `unsloth/Qwen2.5-3B-Instruct-bnb-4bit` | +| ๐Ÿ”ง Fine-tuning method | QLoRA | +| ๐ŸŽ›๏ธ LoRA rank | 16 | +| ๐ŸŽ›๏ธ LoRA alpha | 16 | +| ๐Ÿงฉ Target modules | q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj | +| ๐Ÿ“Š Training data | 6,354 QA pairs โ€” 1,059 sections ร— 6 question types | +| ๐Ÿ” Epochs | 3 | +| ๐Ÿ“ฆ Batch size (effective) | 2 | +| ๐Ÿ“ˆ Learning rate | 2e-4 | +| โš™๏ธ Optimizer | adamw_8bit | +| ๐Ÿ’ป Hardware | Google Colab T4 GPU | +| ๐Ÿ› ๏ธ Framework | Unsloth + TRL SFTTrainer | +| ๐Ÿ’ฌ Prompt format | ChatML | + +--- + +## ๐Ÿ“Š Training Dataset + +| ๐Ÿ“‚ Dataset | ๐Ÿ”— Link | +|---|---| +| Indian Legal QA โ€” BNS + BNSS + BSA 2023 | [GSMS-B/Indian-Legal-QA-BNS-BNSS-BSA](https://huggingface.co/datasets/GSMS-B/Indian-Legal-QA-BNS-BNSS-BSA) | + +**6 question types per section:** +`definitional_topic` ยท `definitional_section` ยท `scenario` ยท `elements` ยท `exceptions` ยท `consequence` + +--- + +## ๐Ÿ‘ค Author + +**GSMS-B** โ€” Bugatha Ganasyam Mani Sankar +๐Ÿค— [Hugging Face Profile](https://huggingface.co/GSMS-B) + +--- + +## โš ๏ธ Disclaimer + +This model is intended for **research and educational purposes only**. It does not constitute legal advice. Outputs should not be relied upon for any legal decision without review by a qualified legal professional. The model's responses reflect patterns in training data and may contain errors or omissions. + +--- + +*โšก Fine-tuned using [Unsloth](https://github.com/unslothai/unsloth) for training efficiency.* \ No newline at end of file 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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You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\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\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\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\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\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 {{- '\\n\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n\\n' }}\n {{- message.content }}\n {{- '\\n' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n" +} \ No newline at end of file