Instructions to use VERSIL91/1c3701b4-7d0a-4c75-ad20-dc76160024ef with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use VERSIL91/1c3701b4-7d0a-4c75-ad20-dc76160024ef with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceM4/tiny-random-LlamaForCausalLM") model = PeftModel.from_pretrained(base_model, "VERSIL91/1c3701b4-7d0a-4c75-ad20-dc76160024ef") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from VERSIL91/1c3701b4-7d0a-4c75-ad20-dc76160024ef: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/VERSIL91/1c3701b4-7d0a-4c75-ad20-dc76160024ef/resolve/main/training_args.bin
- Command line
-
hf download hf://VERSIL91/1c3701b4-7d0a-4c75-ad20-dc76160024ef/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/VERSIL91/1c3701b4-7d0a-4c75-ad20-dc76160024ef/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 061fca65f8fe81a7559d1691b0a77736f3996d23659a462926d191eef5022de5
- Size of remote file:
- 6.78 kB
- SHA256:
- ec65ff09a7cb30674870ca981d98722c8fcfb541ce9a3697fa474d35a2513035
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