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Model: phamthanhfd/contract-analysis-qwen2.5-3b
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2026-07-28 23:50:25 +08:00
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---
language:
- en
license: apache-2.0
base_model: Qwen/Qwen2.5-3B-Instruct
tags:
- legal
- contract-analysis
- qwen2.5
- text-generation
datasets:
- theatticusproject/cuad-qa
pipeline_tag: text-generation
---
# Contract Analysis — Qwen2.5-3B (Merged)
> LoRA adapter nhẹ hơn: [phamthanhfd/contract-analysis-lora-adapter](https://huggingface.co/phamthanhfd/contract-analysis-lora-adapter)
## Quick Start
```python
from transformers import pipeline
pipe = pipeline("text-generation", model="phamthanhfd/contract-analysis-qwen2.5-3b", device_map="auto")
messages = [
{"role":"system","content":"You are a legal contract expert. Return JSON with category and summary."},
{"role":"user","content":"Analyze: The employee shall not disclose confidential information."}
]
result = pipe(messages, max_new_tokens=150, temperature=0.1)
print(result[0]["generated_text"][-1]["content"])
```

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{%- 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 <tools></tools> XML tags:\n<tools>" }}
{%- for tool in tools %}
{{- "\n" }}
{{- tool | tojson }}
{%- endfor %}
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|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<tool_call>\n{"name": "' }}
{{- tool_call.name }}
{{- '", "arguments": ' }}
{{- tool_call.arguments | tojson }}
{{- '}\n</tool_call>' }}
{%- endfor %}
{{- '<|im_end|>\n' }}
{%- elif message.role == "tool" %}
{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
{{- '<|im_start|>user' }}
{%- endif %}
{{- '\n<tool_response>\n' }}
{{- message.content }}
{{- '\n</tool_response>' }}
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
{{- '<|im_end|>\n' }}
{%- endif %}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|im_start|>assistant\n' }}
{%- endif %}

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{
"architectures": [
"Qwen2ForCausalLM"
],
"attention_dropout": 0.0,
"bos_token_id": 151643,
"dtype": "float16",
"eos_token_id": 151645,
"hidden_act": "silu",
"hidden_size": 2048,
"initializer_range": 0.02,
"intermediate_size": 11008,
"layer_types": [
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"max_position_embeddings": 32768,
"max_window_layers": 70,
"model_type": "qwen2",
"num_attention_heads": 16,
"num_hidden_layers": 36,
"num_key_value_heads": 2,
"pad_token_id": null,
"rms_norm_eps": 1e-06,
"rope_parameters": {
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"rope_type": "default"
},
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"tie_word_embeddings": true,
"transformers_version": "5.0.0",
"use_cache": true,
"use_sliding_window": false,
"vocab_size": 151936
}

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"do_sample": true,
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"pad_token_id": 151643,
"repetition_penalty": 1.05,
"temperature": 0.7,
"top_k": 20,
"top_p": 0.8,
"transformers_version": "5.0.0"
}

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{
"add_prefix_space": false,
"backend": "tokenizers",
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"clean_up_tokenization_spaces": false,
"eos_token": "<|im_end|>",
"errors": "replace",
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"tokenizer_class": "Qwen2Tokenizer",
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}