Instructions to use trangtrannnnn/aeebfdf1-a09e-488f-8a00-6f39f7be10be with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use trangtrannnnn/aeebfdf1-a09e-488f-8a00-6f39f7be10be 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, "trangtrannnnn/aeebfdf1-a09e-488f-8a00-6f39f7be10be") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a42d63aa2c4ba9dae0349d029e4835bdbeb2b4a9e68090d2d33e74ad2f160eb
- Size of remote file:
- 6.78 kB
- SHA256:
- 66ecea9f24d8d33f49d2edcd837b4edf2ffcc9cc12a29ce812a476214119a5f5
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