Instructions to use Aivesa/c54c306a-c851-4242-bb27-3011d64be847 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Aivesa/c54c306a-c851-4242-bb27-3011d64be847 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("peft-internal-testing/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "Aivesa/c54c306a-c851-4242-bb27-3011d64be847") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Aivesa/c54c306a-c851-4242-bb27-3011d64be847: direct link, hf CLI and curl.
- Browser
- Download file 6.9 kB
-
https://huggingface.co/Aivesa/c54c306a-c851-4242-bb27-3011d64be847/resolve/main/training_args.bin
- Command line
-
hf download hf://Aivesa/c54c306a-c851-4242-bb27-3011d64be847/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Aivesa/c54c306a-c851-4242-bb27-3011d64be847/resolve/main/training_args.bin
6.9 kB
- Xet hash:
- 62f22e1053045dac0cfaf484535662b60353773d7e0f81dd4411b6c96de6a805
- Size of remote file:
- 6.9 kB
- SHA256:
- 9a1c10863c73b4795e0c1b3b64d79fbc9729192213dbd3d5bee5c75fa4c14252
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