Instructions to use gavrilstep/9da99aa7-a7c0-4c89-95e4-45d78b1ce056 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gavrilstep/9da99aa7-a7c0-4c89-95e4-45d78b1ce056 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("lmsys/vicuna-13b-v1.5") model = PeftModel.from_pretrained(base_model, "gavrilstep/9da99aa7-a7c0-4c89-95e4-45d78b1ce056") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b37531b93094787d09782755cf917f41cfc4655ce32b038474b46e0c94c2d74
- Size of remote file:
- 14.2 kB
- SHA256:
- de242d860410212dad7963a977a426622dce916dd2538c73b3e727b0142f3263
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