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.gitattributes CHANGED
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stage1_external_research/README.md ADDED
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+ ---
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+ base_model: NousResearch/Hermes-3-Llama-3.1-8B
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+ library_name: peft
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+ model_name: stage1_external_research
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+ tags:
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+ - base_model:adapter:NousResearch/Hermes-3-Llama-3.1-8B
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+ - lora
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+ - sft
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+ - transformers
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+ - trl
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+ licence: license
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+ pipeline_tag: text-generation
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+ ---
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+
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+ # Model Card for stage1_external_research
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+
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+ This model is a fine-tuned version of [NousResearch/Hermes-3-Llama-3.1-8B](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B).
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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="None", 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 SFT.
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+
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+ ### Framework versions
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+
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+ - PEFT 0.21.0
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+ - TRL: 1.13.0
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+ - Transformers: 5.17.0
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+ - Pytorch: 2.14.0
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+ - Datasets: 5.0.1
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+ - Tokenizers: 0.23.2
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+
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+ ## Citations
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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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+ @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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+ {{bos_token}}{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system
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+ You are a helpful assistant.<|im_end|>
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+ ' }}{% endif %}{{'<|im_start|>' + message['role'] + '
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