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Model: RuudFontys/socratic-tutor-qwen2.5 Source: Original Platform
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Socratic-Tutor-Qwen2.5_Hf-7.6B-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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Modelfile
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# Socratic Tutor Modelfile for Ollama
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FROM ./Socratic-Tutor-Qwen2.5_Hf-7.6B-Q8_0.gguf
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TEMPLATE """{{ if .System }}<|im_start|>system
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{{ .System }}<|im_end|>
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{{ end }}{{ if .Prompt }}<|im_start|>user
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{{ .Prompt }}<|im_end|>
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{{ end }}<|im_start|>assistant
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{{ .Response }}<|im_end|>
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"""
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PARAMETER temperature 0.7
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PARAMETER top_p 0.9
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PARAMETER top_k 40
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SYSTEM """You are Socrates, a wise and patient tutor. Your goal is not to give answers, but to guide the user to their own understanding through a series of thoughtful questions. Respond to the user's statements by asking probing questions that challenge their assumptions, clarify their thinking, and lead them toward the correct conclusion. Never provide a direct answer unless explicitly asked."""
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README.md
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README.md
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---
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language:
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- en
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license: apache-2.0
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base_model: Qwen/Qwen2.5-7B-Instruct
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tags:
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- qwen2.5
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- fine-tuned
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- socratic-method
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- education
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- tutoring
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- dialogue
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- peft
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- lora
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library_name: transformers
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pipeline_tag: text-generation
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model_type: qwen2
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datasets:
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- synthetic
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metrics:
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- perplexity
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widget:
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- example_title: "Learning Question"
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text: |
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<|im_start|>system
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You are a Socratic tutor who guides learning through questioning. Your role is to help students discover insights themselves by asking probing questions rather than providing direct answers.<|im_end|>
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<|im_start|>user
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Can you explain photosynthesis to me?<|im_end|>
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<|im_start|>assistant
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inference:
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parameters:
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max_new_tokens: 256
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temperature: 0.7
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do_sample: true
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top_p: 0.9
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---
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# 🎭 Socratic Tutor - Qwen2.5 Fine-tuned
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A fine-tuned Qwen2.5-7B model designed to act as a Socratic tutor, guiding learning through questioning rather than providing direct answers.
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## Model Description
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This model has been fine-tuned on synthetic Socratic dialogue data to embody the teaching philosophy of Socrates - helping students discover insights themselves through probing questions and guided inquiry.
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### Key Features
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- **Socratic Method**: Asks thought-provoking questions to guide learning
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- **Educational Focus**: Designed for tutoring and educational conversations
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- **Based on Qwen2.5-7B**: Built on Alibaba's powerful instruction-following model
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- **LoRA Fine-tuning**: Efficiently trained using Low-Rank Adaptation
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## Training Details
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- **Base Model**: Qwen/Qwen2.5-7B-Instruct
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- **Training Method**: LoRA (Low-Rank Adaptation)
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- **Training Data**: 350 synthetic Socratic dialogues
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- **Training Duration**: 3 epochs
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- **Final Loss**: 1.16 (down from 4.86)
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### Training Configuration
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- LoRA rank: 16
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- Learning rate: 0.0002
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- Batch size: 16 (effective)
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- Max sequence length: 2048 tokens
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## Available Formats
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### HuggingFace Format (15.2GB)
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The full precision model in standard HuggingFace format.
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### GGUF Format (4.4GB)
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**File**: `socratic-tutor-v2-q4_k_m.gguf`
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- **Quantization**: Q4_K_M (4-bit mixed quantization)
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- **Size**: 4.4GB (down from 15GB)
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- **Quality**: Excellent balance of size and performance
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- **Compatible with**: llama.cpp, Ollama, and other GGUF-compatible tools
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> **Important**: The GGUF file contains the default Qwen2.5 chat template. To activate Socratic tutoring behavior, you must provide the custom system prompt shown below when using the model.
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## Usage
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### HuggingFace Transformers
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("RuudFontys/socratic-tutor-qwen2.5")
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tokenizer = AutoTokenizer.from_pretrained("RuudFontys/socratic-tutor-qwen2.5")
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# Example conversation
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messages = [
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{"role": "system", "content": "You are a Socratic tutor who guides learning through questioning. Your role is to help students discover insights themselves by asking probing questions rather than providing direct answers."},
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{"role": "user", "content": "Can you explain photosynthesis to me?"}
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]
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inputs = tokenizer.apply_chat_template(messages, return_tensors="pt")
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outputs = model.generate(inputs, max_new_tokens=256, temperature=0.7)
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response = tokenizer.decode(outputs[0], skip_special_tokens=True)
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print(response)
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```
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### GGUF with llama.cpp
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||||
```bash
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# Download the GGUF file
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wget https://huggingface.co/RuudFontys/socratic-tutor-qwen2.5/resolve/main/socratic-tutor-v2-q4_k_m.gguf
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# Run with llama.cpp
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./llama-cli -m socratic-tutor-v2-q4_k_m.gguf \
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--system-prompt "You are a Socratic tutor who guides learning through questioning. Your role is to help students discover insights themselves by asking probing questions rather than providing direct answers." \
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--chat
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```
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### Recommended System Prompt
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For best results, use this system prompt:
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||||
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||||
```
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||||
You are a Socratic tutor who guides learning through questioning. Your role is to help students discover insights themselves by asking probing questions rather than providing direct answers.
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||||
|
||||
Key principles:
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||||
- Ask thought-provoking questions that lead students to discover answers themselves
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||||
- Avoid giving direct explanations unless absolutely necessary
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||||
- Build on student responses with follow-up questions
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||||
- Help students think critically and make connections
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||||
- Guide them through reasoning processes step by step
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- Encourage curiosity and deeper exploration of topics
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Remember: The goal is not to show how much you know, but to help the student learn through their own discovery.
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```
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## Example Interactions
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||||
**Student**: "Why is my boxplot showing outliers?"
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**Tutor**: "Outliers are beyond 1.5×IQR from the quartiles. Which values exceed that threshold in your data?"
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||||
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**Student**: "How does machine learning work?"
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**Tutor**: "What do you think it means for a machine to 'learn' from data? How might that differ from how humans learn?"
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||||
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## Intended Use
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||||
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||||
This model is designed for:
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||||
- Educational tutoring and guidance
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||||
- Socratic dialogue practice
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||||
- Critical thinking development
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||||
- Question-based learning approaches
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||||
## Limitations
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||||
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||||
- May not provide direct answers when they would be more appropriate
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- Performance depends on the quality of input questions
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||||
- Limited to the knowledge in the base Qwen2.5 model
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## Citation
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||||
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||||
If you use this model, please cite:
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||||
```
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||||
@misc{socratic-tutor-qwen25,
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||||
title={Socratic Tutor: A Fine-tuned Qwen2.5 Model for Educational Dialogue},
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||||
author={RuudFontys},
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||||
year={2025},
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||||
url={https://huggingface.co/RuudFontys/socratic-tutor-qwen2.5}
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||||
}
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||||
```
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||||
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||||
## License
|
||||
|
||||
This model inherits the license from the base Qwen2.5 model. Please refer to the original model's licensing terms.
|
||||
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added_tokens.json
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chat_template.jinja
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{%- if tools %}
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||||
{{- '<|im_start|>system\n' }}
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||||
{%- if messages[0]['role'] == 'system' %}
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||||
{{- messages[0]['content'] }}
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||||
{%- else %}
|
||||
{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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||||
{%- 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>" }}
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{%- for tool in tools %}
|
||||
{{- "\n" }}
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||||
{{- tool | tojson }}
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{%- endfor %}
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{{- "\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" }}
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||||
{%- else %}
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||||
{%- if messages[0]['role'] == 'system' %}
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||||
{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
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{%- else %}
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||||
{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
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||||
{%- endif %}
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||||
{%- endif %}
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||||
{%- for message in messages %}
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||||
{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
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||||
{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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||||
{%- elif message.role == "assistant" %}
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||||
{{- '<|im_start|>' + message.role }}
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||||
{%- if message.content %}
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||||
{{- '\n' + message.content }}
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||||
{%- endif %}
|
||||
{%- for tool_call in message.tool_calls %}
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||||
{%- if tool_call.function is defined %}
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||||
{%- set tool_call = tool_call.function %}
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||||
{%- endif %}
|
||||
{{- '\n<tool_call>\n{"name": "' }}
|
||||
{{- tool_call.name }}
|
||||
{{- '", "arguments": ' }}
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||||
{{- tool_call.arguments | tojson }}
|
||||
{{- '}\n</tool_call>' }}
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||||
{%- endfor %}
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||||
{{- '<|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") %}
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||||
{{- '<|im_end|>\n' }}
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||||
{%- endif %}
|
||||
{%- endif %}
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||||
{%- endfor %}
|
||||
{%- if add_generation_prompt %}
|
||||
{{- '<|im_start|>assistant\n' }}
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||||
{%- endif %}
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||||
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config.json
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config.json
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{
|
||||
"architectures": [
|
||||
"Qwen2ForCausalLM"
|
||||
],
|
||||
"attention_dropout": 0.0,
|
||||
"dtype": "bfloat16",
|
||||
"eos_token_id": 151645,
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"hidden_act": "silu",
|
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"hidden_size": 3584,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 18944,
|
||||
"layer_types": [
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
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"full_attention",
|
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"full_attention",
|
||||
"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention"
|
||||
],
|
||||
"max_position_embeddings": 32768,
|
||||
"max_window_layers": 28,
|
||||
"model_type": "qwen2",
|
||||
"num_attention_heads": 28,
|
||||
"num_hidden_layers": 28,
|
||||
"num_key_value_heads": 4,
|
||||
"pad_token_id": 151654,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 1000000.0,
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": false,
|
||||
"transformers_version": "4.56.1",
|
||||
"unsloth_fixed": true,
|
||||
"unsloth_version": "2025.9.5",
|
||||
"use_cache": true,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 152064
|
||||
}
|
||||
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generation_config.json
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{
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"do_sample": true,
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"eos_token_id": [
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],
|
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"max_length": 32768,
|
||||
"pad_token_id": 151654,
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||||
"repetition_penalty": 1.05,
|
||||
"temperature": 0.7,
|
||||
"top_k": 20,
|
||||
"top_p": 0.8,
|
||||
"transformers_version": "4.56.1"
|
||||
}
|
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merges.txt
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model.safetensors.index.json
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|
||||
"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
|
||||
}
|
||||
},
|
||||
"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,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 32768,
|
||||
"pad_token": "<|vision_pad|>",
|
||||
"padding_side": "right",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
31
update_prompt.py
Normal file
31
update_prompt.py
Normal file
@@ -0,0 +1,31 @@
|
||||
from transformers import AutoTokenizer
|
||||
|
||||
# Load the tokenizer from the Hub
|
||||
model_id = "Qwen/Qwen2-7B-Instruct"
|
||||
print(f"Loading tokenizer for '{model_id}' from the Hub...")
|
||||
tokenizer = AutoTokenizer.from_pretrained(model_id)
|
||||
|
||||
# This is the key change: we're targeting the cloned repo for saving
|
||||
model_dir = "/workspace/socratic-tutor-qwen2.5"
|
||||
|
||||
socratic_system_prompt = (
|
||||
"You are Socrates, a wise and patient tutor. Your goal is not to give answers, "
|
||||
"but to guide the user to their own understanding through a series of thoughtful questions. "
|
||||
"Respond to the user's statements by asking probing questions that challenge their assumptions, "
|
||||
"clarify their thinking, and lead them toward the correct conclusion. "
|
||||
"Never provide a direct answer unless explicitly asked."
|
||||
)
|
||||
|
||||
new_chat_template = (
|
||||
"{% for message in messages %}"
|
||||
"{% if loop.first and message['role'] != 'system' %}"
|
||||
"{{ '<|im_start|>system\\n' + '''" + socratic_system_prompt + "''' + '<|im_end|>\\n' }}"
|
||||
"{% endif %}"
|
||||
"{{ '<|im_start|>' + message['role'] + '\\n' + message['content'] + '<|im_end|>\\n' }}"
|
||||
"{% endfor %}"
|
||||
"{% if add_generation_prompt %}{{ '<|im_start|>assistant\\n' }}{% endif %}"
|
||||
)
|
||||
|
||||
tokenizer.chat_template = new_chat_template
|
||||
tokenizer.save_pretrained(model_dir)
|
||||
print(f"✅ Tokenizer in '{model_dir}' updated with the Socratic prompt.")
|
||||
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