Instructions to use cwaud/37bc5eb3-855c-4e9e-ba2f-843c1c30acbe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cwaud/37bc5eb3-855c-4e9e-ba2f-843c1c30acbe 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, "cwaud/37bc5eb3-855c-4e9e-ba2f-843c1c30acbe") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14defd04d65c74779fc3dc41be2886af86f2466b547682433db2cc166e43a4a9
- Size of remote file:
- 84 MB
- SHA256:
- f3e1f15437622a49b24a8f01ec21e3bebbbf61d437494cdb0ecdf9ef8751fdc9
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