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 training_args.bin from sergioalves/93433971-bb9a-4b57-89e3-af3b88fd7571: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/sergioalves/93433971-bb9a-4b57-89e3-af3b88fd7571/resolve/main/training_args.bin
- Command line
-
hf download hf://sergioalves/93433971-bb9a-4b57-89e3-af3b88fd7571/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sergioalves/93433971-bb9a-4b57-89e3-af3b88fd7571/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 91eb16c305d6e5a65f509a716961f7ec4a558d4232d09e8e411a50fe14433334
- Size of remote file:
- 6.84 kB
- SHA256:
- 2cac631d145b6906faee6718f5d0afd572907b58138f915f1dc5931bc5ca3680
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