| | --- |
| | base_model: unsloth/LFM2-8B-A1B |
| | library_name: transformers |
| | model_name: model_checkpoints |
| | tags: |
| | - generated_from_trainer |
| | - trl |
| | - unsloth |
| | - sft |
| | licence: license |
| | --- |
| | |
| | # Model Card for model_checkpoints |
| | |
| | This model is a fine-tuned version of [unsloth/LFM2-8B-A1B](https://huggingface.co/unsloth/LFM2-8B-A1B). |
| | 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="Ba2han/model-translator-lfm", 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/batuhan409/huggingface/runs/e10j1inz) |
| | |
| | |
| | This model was trained with SFT. |
| | |
| | ### Framework versions |
| | |
| | - TRL: 0.24.0 |
| | - Transformers: 4.57.0.dev0 |
| | - Pytorch: 2.9.1 |
| | - Datasets: 4.3.0 |
| | - Tokenizers: 0.22.1 |
| | |
| | ## 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 Gallou{\'e}dec}, |
| | year = 2020, |
| | journal = {GitHub repository}, |
| | publisher = {GitHub}, |
| | howpublished = {\url{https://github.com/huggingface/trl}} |
| | } |
| | ``` |
