Instructions to use romainnn/01a286fd-ea04-43ca-bf49-50711b0ac07d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use romainnn/01a286fd-ea04-43ca-bf49-50711b0ac07d with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("JackFram/llama-68m") model = PeftModel.from_pretrained(base_model, "romainnn/01a286fd-ea04-43ca-bf49-50711b0ac07d") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f52dcb9ea8687b1a70020dea1701eb0f31270e1333b9273fb65a1657e5e7e6aa
- Size of remote file:
- 9.05 MB
- SHA256:
- 1c468027529d09fef9e9bd69bb6a34b440a506d12614971720053c51e8c1686c
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