Instructions to use orange67/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use orange67/results with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("orange67/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
llama-3-lora-finetuned
Browse files- README.md +1 -1
- adapter_config.json +2 -2
- adapter_model.safetensors +1 -1
- training_args.bin +1 -1
README.md
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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/orange67-purdue-university/huggingface/runs/
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This model was trained with SFT.
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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/orange67-purdue-university/huggingface/runs/cphu93ig)
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This model was trained with SFT.
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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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"
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"v_proj",
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"o_proj",
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"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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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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"v_proj",
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"o_proj",
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"q_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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adapter_model.safetensors
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training_args.bin
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