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pratimassaravanan/clinical-sft-grpo

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  1. .gitattributes +1 -0
  2. README.md +67 -0
  3. adapter_config.json +48 -0
  4. adapter_model.safetensors +3 -0
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.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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1
+ ---
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+ library_name: transformers
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+ model_name: grpo
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+ tags:
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+ - generated_from_trainer
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+ - trl
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+ - grpo
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+ - hf_jobs
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+ licence: license
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+ ---
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+
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+ # Model Card for grpo
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+
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+ This model is a fine-tuned version of [None](https://huggingface.co/None).
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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="pratimassaravanan/grpo", 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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+
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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: 1.2.0
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+ - Transformers: 5.6.2
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+ - Pytorch: 2.11.0
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+ - Datasets: 4.8.4
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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},
54
+ }
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+ ```
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+
57
+ Cite TRL as:
58
+
59
+ ```bibtex
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+ @software{vonwerra2020trl,
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+ title = {{TRL: Transformers Reinforcement Learning}},
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+ author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
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+ license = {Apache-2.0},
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+ url = {https://github.com/huggingface/trl},
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+ year = {2020}
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+ }
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+ ```
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+ {
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+ "alora_invocation_tokens": null,
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+ "alpha_pattern": {},
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+ {%- if tools %}
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+ {{- '<|im_start|>system\n' }}
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+ {%- if messages[0].role == 'system' %}
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+ {{- messages[0].content + '\n\n' }}
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+ {%- endif %}
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+ {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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+ {%- for tool in tools %}
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+ {{- "\n" }}
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+ {{- tool | tojson }}
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+ {%- if loop.last or (not loop.last and reasoning_content) %}
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+ {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
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+ {%- else %}
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+ {{- '<|im_start|>' + message.role + '\n' + content }}
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+ {%- if (loop.first and content) or (not loop.first) %}
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