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--- |
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base_model: Aratako/Llama-Gemma-2-27b-SimPO-trial3 |
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library_name: transformers |
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model_name: fft-simpo3-iterative-iter1 |
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tags: |
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- generated_from_trainer |
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- axolotl |
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- trl |
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- cpo |
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licence: license |
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--- |
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# Model Card for fft-simpo3-iterative-iter1 |
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This model is a fine-tuned version of [Aratako/Llama-Gemma-2-27b-SimPO-trial3](https://huggingface.co/Aratako/Llama-Gemma-2-27b-SimPO-trial3). |
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It has been trained using [TRL](https://github.com/huggingface/trl). |
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## Quick start |
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```python |
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from transformers import pipeline |
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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?" |
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generator = pipeline("text-generation", model="Aratako/fft-simpo3-iterative-iter1", device="cuda") |
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] |
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print(output["generated_text"]) |
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``` |
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## Training procedure |
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[<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/aratako-lm/27b-fft/runs/g9va2r0s) |
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This model was trained with CPO, a method introduced in [Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation](https://huggingface.co/papers/2401.08417). |
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### Framework versions |
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- TRL: 0.12.0 |
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- Transformers: 4.46.3 |
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- Pytorch: 2.3.1+cu121 |
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- Datasets: 3.1.0 |
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- Tokenizers: 0.20.3 |
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## Citations |
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Cite CPO as: |
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```bibtex |
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@inproceedings{xu2024contrastive, |
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title = {{Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation}}, |
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author = {Haoran Xu and Amr Sharaf and Yunmo Chen and Weiting Tan and Lingfeng Shen and Benjamin Van Durme and Kenton Murray and Young Jin Kim}, |
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year = 2024, |
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booktitle = {Forty-first International Conference on Machine Learning, {ICML} 2024, Vienna, Austria, July 21-27, 2024}, |
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publisher = {OpenReview.net}, |
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url = {https://openreview.net/forum?id=51iwkioZpn} |
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} |
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``` |
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Cite TRL as: |
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```bibtex |
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@misc{vonwerra2022trl, |
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title = {{TRL: Transformer Reinforcement Learning}}, |
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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}, |
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year = 2020, |
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journal = {GitHub repository}, |
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publisher = {GitHub}, |
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howpublished = {\url{https://github.com/huggingface/trl}} |
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} |
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``` |