---
library_name: transformers
tags:
- trl
- sft
datasets:
- qwedsacf/grade-school-math-instructions
language:
- en
base_model:
- Qwen/Qwen2.5-3B
---

<img src="https://huggingface.co/entfane/math-professor-3B/resolve/main/math-professor-image.png" width="300" height="300"/>


# Math Professor 3B

This model is a math instruction fine-tuned version of Qwen2.5-3B model.

### Fine-tuning dataset

Model was fine-tuned on [qwedsacf/grade-school-math-instructions](https://huggingface.co/datasets/qwedsacf/grade-school-math-instructions) instruction dataset.

### Inference

```python
!pip install transformers accelerate

from transformers import AutoTokenizer, AutoModelForCausalLM

model_name = "entfane/math-professor-3B"

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

messages = [
    {"role": "user", "content": "What's the derivative of 2x^2?"}
]

input = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
encoded_input = tokenizer(input, return_tensors = "pt").to(model.device)
output = model.generate(**encoded_input, max_new_tokens=1024)
print(tokenizer.decode(output[0], skip_special_tokens=False))
```