Instructions to use nhung01/f0fcc583-c1c6-46df-b638-dbf595dfa987 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung01/f0fcc583-c1c6-46df-b638-dbf595dfa987 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-2-7b-chat") model = PeftModel.from_pretrained(base_model, "nhung01/f0fcc583-c1c6-46df-b638-dbf595dfa987") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a944d8831fde2c0053f50f3a093af52af32910fb0d5aaf37a7618d7d0f603b12
- Size of remote file:
- 80.1 MB
- SHA256:
- d7cec0b9307aeff90f5894ff4626deb9b18e5a7a3336ac03df533204bcd3d8ba
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