33 lines
1.3 KiB
Markdown
33 lines
1.3 KiB
Markdown
# qwen-2.5-instruct-sdft-science
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This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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This model has been trained using [Self-Distillation Fine-Tuning](https://arxiv.org/abs/2601.19897) on the Released Science dataset.
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Within this repo, you can find `/eval` directory, containing the evaluation results on the Tool Use evaluation split.
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The model has been trained for 300 steps (the best checkopint we have obtained), scoring 64.5% on the evaluation set.
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Our Reproduction Report of Tool Use: https://github.com/KickItLikeShika/sdft-reproduction-note
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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="KickItLikeShika/qwen-2.5-7b-instruct-sdft-science", 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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W&B Report Tool Use Reproduction Report
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https://api.wandb.ai/links/egyttsteam/d97ty5d9
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### Framework versions
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- TRL: 0.24.0
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- Transformers: 4.57.1
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- Pytorch: 2.9.0
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- Datasets: 4.3.0
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- Tokenizers: 0.22.2
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