Instructions to use kk-aivio/de723172-3661-4906-ae0d-e9e8237f9998 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kk-aivio/de723172-3661-4906-ae0d-e9e8237f9998 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, "kk-aivio/de723172-3661-4906-ae0d-e9e8237f9998") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kk-aivio/de723172-3661-4906-ae0d-e9e8237f9998: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/kk-aivio/de723172-3661-4906-ae0d-e9e8237f9998/resolve/main/training_args.bin
- Command line
-
hf download hf://kk-aivio/de723172-3661-4906-ae0d-e9e8237f9998/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kk-aivio/de723172-3661-4906-ae0d-e9e8237f9998/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- e016ca8ff62e4902062707146d8be272c664ca0d990d88a2c01e7009b8aefc66
- Size of remote file:
- 6.78 kB
- SHA256:
- 5d17a3ef076f34e0315112f7a2a0034e013edab6887a6f8d2c5559b23d4da8b3
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