Instructions to use nhung03/349b95fc-e53d-42a5-9fd5-513993cfa741 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung03/349b95fc-e53d-42a5-9fd5-513993cfa741 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Nous-Capybara-7B-V1") model = PeftModel.from_pretrained(base_model, "nhung03/349b95fc-e53d-42a5-9fd5-513993cfa741") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd7342e65468c5b6c8679521f7d6f55b3d091a336f8aff0117950b15a184397d
- Size of remote file:
- 6.78 kB
- SHA256:
- 1d61b94bdb4a57eda9b406677dfc75109557e4f5495ce7b53956b29e6b05ade3
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