Instructions to use atifquamar07/llama-3.1-8b-HH-DPO-0.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use atifquamar07/llama-3.1-8b-HH-DPO-0.5 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("atifquamar07/llama-3.1-8b-HH-DPO-0.5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 10000
Browse files- README.md +2 -2
- adapter_config.json +1 -1
- adapter_model.safetensors +1 -1
- training_args.bin +1 -1
README.md
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model_name: llama-3.1-8b-HH-DPO-0.5
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tags:
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- generated_from_trainer
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- dpo
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- trl
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licence: license
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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/2this0username0isnt2allowed-indian-institute-of-science/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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model_name: llama-3.1-8b-HH-DPO-0.5
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tags:
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- generated_from_trainer
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- trl
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- dpo
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licence: license
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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/2this0username0isnt2allowed-indian-institute-of-science/huggingface/runs/fe5t9krz)
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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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adapter_config.json
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"k_proj",
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"o_proj",
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"q_proj",
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"v_proj"
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],
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"task_type": "CAUSAL_LM",
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"q_proj",
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"k_proj",
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"o_proj",
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"v_proj"
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],
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"task_type": "CAUSAL_LM",
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adapter_model.safetensors
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size 109086416
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size 109086416
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training_args.bin
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size 6737
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