Model save
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README.md
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---
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base_model: RyanYr/self-correct_Llama-3.2-3B-
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library_name: transformers
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model_name: self-correct_Llama-3.2-3B-
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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_Llama-3.2-3B-
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This model is a fine-tuned version of [RyanYr/self-correct_Llama-3.2-3B-
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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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_Llama-3.2-3B-
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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_Llama-3.2-3B-Instruct_metaMathQA_dpo_iter6
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library_name: transformers
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model_name: self-correct_Llama-3.2-3B-Instruct_metaMathQA_dpo_iter7
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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_Llama-3.2-3B-Instruct_metaMathQA_dpo_iter7
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This model is a fine-tuned version of [RyanYr/self-correct_Llama-3.2-3B-Instruct_metaMathQA_dpo_iter6](https://huggingface.co/RyanYr/self-correct_Llama-3.2-3B-Instruct_metaMathQA_dpo_iter6).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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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_Llama-3.2-3B-Instruct_metaMathQA_dpo_iter7", 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/93v2aobh)
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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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last_checkpoint/config.json
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{
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"_name_or_path": "RyanYr/self-correct_Llama-3.2-3B-
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"architectures": [
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"LlamaForCausalLM"
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],
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{
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"_name_or_path": "RyanYr/self-correct_Llama-3.2-3B-Instruct_metaMathQA_dpo_iter6",
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"architectures": [
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"LlamaForCausalLM"
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],
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last_checkpoint/model-00001-of-00002.safetensors
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last_checkpoint/model-00002-of-00002.safetensors
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