| --- |
| base_model: unsloth/phi-3.5-mini-instruct-bnb-4bit |
| library_name: transformers |
| model_name: code_model |
| tags: |
| - generated_from_trainer |
| - unsloth |
| - trl |
| - sft |
| licence: license |
| --- |
| |
| # Model Card for code_model |
| |
| This model is a fine-tuned version of [unsloth/phi-3.5-mini-instruct-bnb-4bit](https://huggingface.co/unsloth/phi-3.5-mini-instruct-bnb-4bit). |
| It has been trained using [TRL](https://github.com/huggingface/trl). |
| |
| ## Quick start |
| |
| ```python |
| from transformers import pipeline |
| |
| question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?" |
| generator = pipeline("text-generation", model="amakura/code_model", device="cuda") |
| output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] |
| print(output["generated_text"]) |
| ``` |
| |
| ## Training procedure |
| |
| [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/amura-n-a/huggingface/runs/jrg7lvn4) |
| |
| |
| This model was trained with SFT. |
| |
| ### Framework versions |
| |
| - TRL: 0.13.0 |
| - Transformers: 4.47.1 |
| - Pytorch: 2.5.1+cu121 |
| - Datasets: 3.2.0 |
| - Tokenizers: 0.21.0 |
| |
| ## Citations |
| |
| |
| |
| Cite TRL as: |
| |
| ```bibtex |
| @misc{vonwerra2022trl, |
| title = {{TRL: Transformer Reinforcement Learning}}, |
| author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec}, |
| year = 2020, |
| journal = {GitHub repository}, |
| publisher = {GitHub}, |
| howpublished = {\url{https://github.com/huggingface/trl}} |
| } |
| ``` |
