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Model: prithivMLmods/QwQ-LCoT-3B-Instruct Source: Original Platform
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README.md
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---
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license: creativeml-openrail-m
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datasets:
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- amphora/QwQ-LongCoT-130K
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language:
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- en
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base_model:
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- Qwen/Qwen2.5-3B-Instruct
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- text-generation-inference
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- long-CoT
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- safetensors
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- 3B
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- Instruct
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- QwQ
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- Qwen2.5
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---
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### **QwQ-LCoT-3B-Instruct Model Card**
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The **QwQ-LCoT-3B-Instruct** model is a lightweight, instruction-tuned language model designed for complex reasoning and explanation tasks. It is fine-tuned on the **Qwen2.5-3B-Instruct** base model using the **QwQ-LongCoT-130K** dataset, focusing on **long-chain-of-thought (LCoT)** reasoning for enhanced logical comprehension and detailed output generation.
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| **File Name** | **Size** | **Description** | **Upload Status** |
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|----------------------------------------|----------------|-------------------------------------------------|--------------------|
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| `.gitattributes` | 1.57 kB | Specifies LFS tracking for large files. | Uploaded |
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| `README.md` | 267 Bytes | Basic project information file. | Updated |
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| `added_tokens.json` | 657 Bytes | Custom tokens added to the tokenizer. | Uploaded |
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| `config.json` | 859 Bytes | Configuration file for the model. | Uploaded |
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| `generation_config.json` | 281 Bytes | Configuration file for text generation settings.| Uploaded |
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| `merges.txt` | 1.82 MB | Contains the byte-pair encoding (BPE) merges. | Uploaded |
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| `pytorch_model-00001-of-00002.bin` | 4.96 GB | First shard of the model weights in PyTorch format. | Uploaded (LFS) |
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| `pytorch_model-00002-of-00002.bin` | 1.21 GB | Second shard of the model weights in PyTorch format. | Uploaded (LFS) |
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| `pytorch_model.bin.index.json` | 36 kB | Index mapping for sharded model weights. | Uploaded |
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| `special_tokens_map.json` | 644 Bytes | Maps special tokens to their roles. | Uploaded |
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| `tokenizer.json` | 11.4 MB | Serialized tokenizer data. | Uploaded (LFS) |
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| `tokenizer_config.json` | 7.73 kB | Tokenizer configuration settings. | Uploaded |
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| `vocab.json` | 2.78 MB | Vocabulary file for the tokenizer. | Uploaded |
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### **Sample Long CoT:**
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### **Key Features:**
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1. **Long Chain-of-Thought Reasoning:**
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- Specifically designed to generate comprehensive, step-by-step explanations for complex queries.
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2. **Lightweight and Efficient:**
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- With only 3 billion parameters, it is optimized for systems with limited computational resources without compromising reasoning capabilities.
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3. **Instruction Optimization:**
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- Fine-tuned to follow prompts and provide concise, actionable, and structured responses.
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---
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### **Training Details:**
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- **Base Model:** [Qwen2.5-3B-Instruct](#)
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- **Dataset:** [amphora/QwQ-LongCoT-130K](#)
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- Comprising 133,000 annotated samples focusing on logical tasks and structured thinking.
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---
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### **Capabilities:**
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1. **Text Generation:**
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- Provides detailed, structured, and logical text outputs tailored to user prompts.
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2. **Reasoning Tasks:**
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- Solves step-by-step problems in math, logic, and science.
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3. **Educational Assistance:**
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- Generates coherent explanations for academic and research purposes.
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4. **Dialogue and Summarization:**
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- Handles conversational queries and summarizes long documents effectively.
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---
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### **Usage Instructions:**
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1. **Setup:**
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Download all model files and ensure compatibility with the Hugging Face Transformers library.
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2. **Loading the Model:**
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "prithivMLmods/QwQ-LCoT-3B-Instruct"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name)
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```
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3. **Generate Long-Chain Reasoning Outputs:**
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```python
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input_text = "Explain the process of photosynthesis step-by-step."
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inputs = tokenizer(input_text, return_tensors="pt")
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outputs = model.generate(**inputs, max_length=300, temperature=0.5)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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4. **Customize Output Generation:**
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Modify the `generation_config.json` file for different scenarios:
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- **`temperature`**: Controls randomness (lower = deterministic, higher = creative).
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- **`max_length`**: Sets response length.
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- **`top_p`**: Adjusts sampling for diversity in outputs.
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---
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config.json
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"_name_or_path": "unsloth/qwen2.5-3b-instruct-bnb-4bit",
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"architectures": [
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"Qwen2ForCausalLM"
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||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151648": {
|
||||
"content": "<|box_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151649": {
|
||||
"content": "<|box_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151650": {
|
||||
"content": "<|quad_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151651": {
|
||||
"content": "<|quad_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151652": {
|
||||
"content": "<|vision_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151653": {
|
||||
"content": "<|vision_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151654": {
|
||||
"content": "<|vision_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151655": {
|
||||
"content": "<|image_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151665": {
|
||||
"content": "<|PAD_TOKEN|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are Qwen, created by Alibaba Cloud. 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 <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\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\" }}\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<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %} {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\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",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"model_max_length": 32768,
|
||||
"pad_token": "<|PAD_TOKEN|>",
|
||||
"padding_side": "left",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user