Instructions to use nhung01/c7b3afed-dce2-40c7-bed1-fc4a1cd4fe7e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung01/c7b3afed-dce2-40c7-bed1-fc4a1cd4fe7e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Meta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "nhung01/c7b3afed-dce2-40c7-bed1-fc4a1cd4fe7e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ddad77201bf9cac797b5cc6a7443aa03d60b2437900ec3436e79c6994fa422ac
- Size of remote file:
- 84 MB
- SHA256:
- f5ddc20fea621b9b02330a3d81992ee58eb97c83730edd25aa7cc2f30ebeca64
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