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Training in progress, step 50

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.gitattributes CHANGED
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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+ ---
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+ base_model: google/medgemma-1.5-4b-it
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+ library_name: transformers
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+ model_name: transcript-to-note
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+ tags:
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+ - generated_from_trainer
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+ - hf_jobs
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+ - trl
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+ - grpo
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+ licence: license
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+ ---
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+
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+ # Model Card for transcript-to-note
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+
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+ This model is a fine-tuned version of [google/medgemma-1.5-4b-it](https://huggingface.co/google/medgemma-1.5-4b-it).
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+ It has been trained using [TRL](https://github.com/huggingface/trl).
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+
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+ ## Quick start
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+
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+ ```python
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+ from transformers import pipeline
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+
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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="cmcmaster/transcript-to-note", 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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+
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+ ## Training procedure
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+
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+
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+
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+
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+ This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
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+
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+ ### Framework versions
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+
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+ - TRL: 0.27.0
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+ - Transformers: 4.57.6
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+ - Pytorch: 2.9.1
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+ - Datasets: 4.5.0
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+ - Tokenizers: 0.22.2
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+
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+ ## Citations
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+
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+ Cite GRPO as:
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+
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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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+ ```
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+
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+ Cite TRL as:
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+
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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 Gallou{\'e}dec},
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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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+ ```
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+ {{ bos_token }}
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+ {%- if messages[0]['role'] == 'system' -%}
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+ {{ raise_exception("Invalid content type") }}
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+ {%- endif -%}
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+ {{ '<end_of_turn>
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+ ' }}
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