Instructions to use Prience91/lora_sft_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prience91/lora_sft_output with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Prience91/lora_sft_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Prience91/lora_sft_output: direct link, hf CLI and curl.
- Browser
- Download file 5.65 kB
-
https://huggingface.co/Prience91/lora_sft_output/resolve/main/training_args.bin
- Command line
-
hf download hf://Prience91/lora_sft_output/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Prience91/lora_sft_output/resolve/main/training_args.bin
5.65 kB
- Xet hash:
- 8a2c78ce4a0059266ee506e04d643d8ae117beb1a5398196d29be729eb2b542a
- Size of remote file:
- 5.65 kB
- SHA256:
- da75254bb15e8256ab0273070874e83862f373b3fccf9904863b7dc59aea49fb
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