Instructions to use marialvsantiago/5571a358-933b-425b-bd26-d2332be6f75e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use marialvsantiago/5571a358-933b-425b-bd26-d2332be6f75e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.1-Storm-8B") model = PeftModel.from_pretrained(base_model, "marialvsantiago/5571a358-933b-425b-bd26-d2332be6f75e") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from marialvsantiago/5571a358-933b-425b-bd26-d2332be6f75e: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/marialvsantiago/5571a358-933b-425b-bd26-d2332be6f75e/resolve/main/training_args.bin
- Command line
-
hf download hf://marialvsantiago/5571a358-933b-425b-bd26-d2332be6f75e/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/marialvsantiago/5571a358-933b-425b-bd26-d2332be6f75e/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 7cff0634d3784d04550d87431d907301faa70b945c2c99c48c085d76f2545729
- Size of remote file:
- 6.78 kB
- SHA256:
- c511d9397ecd8b7539990151afd4a62c287a41f597ab34a5c4adb7983b3aa060
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