Model save
Browse files- README.md +4 -4
- last_checkpoint/model-00001-of-00009.safetensors +1 -1
- last_checkpoint/model-00002-of-00009.safetensors +1 -1
- last_checkpoint/model-00003-of-00009.safetensors +1 -1
- last_checkpoint/model-00004-of-00009.safetensors +1 -1
- last_checkpoint/model-00005-of-00009.safetensors +1 -1
- last_checkpoint/model-00006-of-00009.safetensors +1 -1
- last_checkpoint/model-00007-of-00009.safetensors +1 -1
- last_checkpoint/model-00008-of-00009.safetensors +1 -1
- last_checkpoint/model-00009-of-00009.safetensors +1 -1
- last_checkpoint/training_args.bin +2 -2
README.md
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---
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base_model: RyanYr/self-correct_mistral-small-it_mMQA_dpo_iter3
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library_name: transformers
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model_name: self-correct_mistral-small-
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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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# Model Card for self-correct_mistral-small-
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This model is a fine-tuned version of [RyanYr/self-correct_mistral-small-it_mMQA_dpo_iter3](https://huggingface.co/RyanYr/self-correct_mistral-small-it_mMQA_dpo_iter3).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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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="RyanYr/self-correct_mistral-small-
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/yyr/huggingface/runs/
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This model was trained with DPO, a method introduced in [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://huggingface.co/papers/2305.18290).
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---
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base_model: RyanYr/self-correct_mistral-small-it_mMQA_dpo_iter3
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library_name: transformers
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model_name: self-correct_mistral-small-it_mMQA_dpo_iter4_beta.05
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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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# Model Card for self-correct_mistral-small-it_mMQA_dpo_iter4_beta.05
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This model is a fine-tuned version of [RyanYr/self-correct_mistral-small-it_mMQA_dpo_iter3](https://huggingface.co/RyanYr/self-correct_mistral-small-it_mMQA_dpo_iter3).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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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="RyanYr/self-correct_mistral-small-it_mMQA_dpo_iter4_beta.05", 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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/yyr/huggingface/runs/9v4u4jit)
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This model was trained with DPO, a method introduced in [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://huggingface.co/papers/2305.18290).
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