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Model: RuudFontys/socratic-tutor-qwen2.5
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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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# Socratic Tutor Modelfile for Ollama
FROM ./Socratic-Tutor-Qwen2.5_Hf-7.6B-Q8_0.gguf
TEMPLATE """{{ if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{ end }}{{ if .Prompt }}<|im_start|>user
{{ .Prompt }}<|im_end|>
{{ end }}<|im_start|>assistant
{{ .Response }}<|im_end|>
"""
PARAMETER temperature 0.7
PARAMETER top_p 0.9
PARAMETER top_k 40
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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---
language:
- en
license: apache-2.0
base_model: Qwen/Qwen2.5-7B-Instruct
tags:
- qwen2.5
- fine-tuned
- socratic-method
- education
- tutoring
- dialogue
- peft
- lora
library_name: transformers
pipeline_tag: text-generation
model_type: qwen2
datasets:
- synthetic
metrics:
- perplexity
widget:
- example_title: "Learning Question"
text: |
<|im_start|>system
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|>
<|im_start|>user
Can you explain photosynthesis to me?<|im_end|>
<|im_start|>assistant
inference:
parameters:
max_new_tokens: 256
temperature: 0.7
do_sample: true
top_p: 0.9
---
# 🎭 Socratic Tutor - Qwen2.5 Fine-tuned
A fine-tuned Qwen2.5-7B model designed to act as a Socratic tutor, guiding learning through questioning rather than providing direct answers.
## Model Description
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.
### Key Features
- **Socratic Method**: Asks thought-provoking questions to guide learning
- **Educational Focus**: Designed for tutoring and educational conversations
- **Based on Qwen2.5-7B**: Built on Alibaba's powerful instruction-following model
- **LoRA Fine-tuning**: Efficiently trained using Low-Rank Adaptation
## Training Details
- **Base Model**: Qwen/Qwen2.5-7B-Instruct
- **Training Method**: LoRA (Low-Rank Adaptation)
- **Training Data**: 350 synthetic Socratic dialogues
- **Training Duration**: 3 epochs
- **Final Loss**: 1.16 (down from 4.86)
### Training Configuration
- LoRA rank: 16
- Learning rate: 0.0002
- Batch size: 16 (effective)
- Max sequence length: 2048 tokens
## Available Formats
### HuggingFace Format (15.2GB)
The full precision model in standard HuggingFace format.
### GGUF Format (4.4GB)
**File**: `socratic-tutor-v2-q4_k_m.gguf`
- **Quantization**: Q4_K_M (4-bit mixed quantization)
- **Size**: 4.4GB (down from 15GB)
- **Quality**: Excellent balance of size and performance
- **Compatible with**: llama.cpp, Ollama, and other GGUF-compatible tools
> **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.
## Usage
### HuggingFace Transformers
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("RuudFontys/socratic-tutor-qwen2.5")
tokenizer = AutoTokenizer.from_pretrained("RuudFontys/socratic-tutor-qwen2.5")
# Example conversation
messages = [
{"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."},
{"role": "user", "content": "Can you explain photosynthesis to me?"}
]
inputs = tokenizer.apply_chat_template(messages, return_tensors="pt")
outputs = model.generate(inputs, max_new_tokens=256, temperature=0.7)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)
```
### GGUF with llama.cpp
```bash
# Download the GGUF file
wget https://huggingface.co/RuudFontys/socratic-tutor-qwen2.5/resolve/main/socratic-tutor-v2-q4_k_m.gguf
# Run with llama.cpp
./llama-cli -m socratic-tutor-v2-q4_k_m.gguf \
--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." \
--chat
```
### Recommended System Prompt
For best results, use this 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.
Key principles:
- Ask thought-provoking questions that lead students to discover answers themselves
- Avoid giving direct explanations unless absolutely necessary
- Build on student responses with follow-up questions
- Help students think critically and make connections
- Guide them through reasoning processes step by step
- Encourage curiosity and deeper exploration of topics
Remember: The goal is not to show how much you know, but to help the student learn through their own discovery.
```
## Example Interactions
**Student**: "Why is my boxplot showing outliers?"
**Tutor**: "Outliers are beyond 1.5×IQR from the quartiles. Which values exceed that threshold in your data?"
**Student**: "How does machine learning work?"
**Tutor**: "What do you think it means for a machine to 'learn' from data? How might that differ from how humans learn?"
## Intended Use
This model is designed for:
- Educational tutoring and guidance
- Socratic dialogue practice
- Critical thinking development
- Question-based learning approaches
## Limitations
- May not provide direct answers when they would be more appropriate
- Performance depends on the quality of input questions
- Limited to the knowledge in the base Qwen2.5 model
## Citation
If you use this model, please cite:
```
@misc{socratic-tutor-qwen25,
title={Socratic Tutor: A Fine-tuned Qwen2.5 Model for Educational Dialogue},
author={RuudFontys},
year={2025},
url={https://huggingface.co/RuudFontys/socratic-tutor-qwen2.5}
}
```
## 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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{%- 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 %}
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{%- 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 %}
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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) %}
{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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{{- '<|im_start|>' + message.role }}
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{{- '\n' + message.content }}
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{%- 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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{
"additional_special_tokens": [
"<|im_start|>",
"<|im_end|>",
"<|object_ref_start|>",
"<|object_ref_end|>",
"<|box_start|>",
"<|box_end|>",
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"<|vision_start|>",
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"<|video_pad|>"
],
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{
"add_bos_token": false,
"add_prefix_space": false,
"added_tokens_decoder": {
"151643": {
"content": "<|endoftext|>",
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},
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"content": "<|file_sep|>",
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}
},
"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": {},
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"padding_side": "right",
"split_special_tokens": false,
"tokenizer_class": "Qwen2Tokenizer",
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}

31
update_prompt.py Normal file
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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

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