Instructions to use nhung03/382bce09-54c8-42a5-8974-235c3735a241 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung03/382bce09-54c8-42a5-8974-235c3735a241 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("lmsys/vicuna-7b-v1.3") model = PeftModel.from_pretrained(base_model, "nhung03/382bce09-54c8-42a5-8974-235c3735a241") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c5b73ce09821ea1964caf8671f9e99be106ed6152f84d011b249b0145ac8b6c
- Size of remote file:
- 6.78 kB
- SHA256:
- 98439b7cf8f8089715b6d1efde346c2ea2debf865b8e28f8c3e028c5629c06a8
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