Instructions to use sergioalves/93433971-bb9a-4b57-89e3-af3b88fd7571 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sergioalves/93433971-bb9a-4b57-89e3-af3b88fd7571 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, "sergioalves/93433971-bb9a-4b57-89e3-af3b88fd7571") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from sergioalves/93433971-bb9a-4b57-89e3-af3b88fd7571: direct link, hf CLI and curl.
- Browser
- Download file 684 MB
-
https://huggingface.co/sergioalves/93433971-bb9a-4b57-89e3-af3b88fd7571/resolve/main/adapter_model.bin
- Command line
-
hf download hf://sergioalves/93433971-bb9a-4b57-89e3-af3b88fd7571/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/sergioalves/93433971-bb9a-4b57-89e3-af3b88fd7571/resolve/main/adapter_model.bin
684 MB
- Xet hash:
- ef0c71867455cad83bae4b936e7323450ae8aed94f95f8f6010ef272c26eb71b
- Size of remote file:
- 684 MB
- SHA256:
- b7555d51aa5e50ce254be6f01890ae47cff97bfd3673e8b9fb71dfcdc1c5de7c
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