Instructions to use bfilar/mql-finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bfilar/mql-finetune with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bfilar/mql-finetune", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- README.md +2 -11
- adapter_config.json +3 -3
- adapter_model.safetensors +2 -2
- training_args.bin +2 -2
README.md
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model_name: mql-finetune
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tags:
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- generated_from_trainer
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- trl
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licence: license
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---
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This model was trained with
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### Framework versions
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## Citations
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Cite GRPO as:
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```bibtex
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@article{shao2024deepseekmath,
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title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
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author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
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year = 2024,
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eprint = {arXiv:2402.03300},
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}
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```
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Cite TRL as:
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model_name: mql-finetune
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tags:
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- generated_from_trainer
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- sft
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- trl
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licence: license
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---
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This model was trained with SFT.
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### Framework versions
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## Citations
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Cite TRL as:
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adapter_config.json
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"gate_proj",
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"o_proj",
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"up_proj",
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"down_proj",
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"k_proj",
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"v_proj",
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"q_proj"
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],
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"target_parameters": null,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"o_proj",
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"down_proj",
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"v_proj",
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"gate_proj",
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"up_proj",
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"k_proj",
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"q_proj"
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],
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"target_parameters": null,
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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size 66127776
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training_args.bin
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size 5713
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