| 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)) | |
| ``` |