Instructions to use hasdal/bfe3df3d-eae6-45b5-8024-1929fbc905fa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use hasdal/bfe3df3d-eae6-45b5-8024-1929fbc905fa with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("tiiuae/Falcon3-1B-Base") model = PeftModel.from_pretrained(base_model, "hasdal/bfe3df3d-eae6-45b5-8024-1929fbc905fa") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hasdal/bfe3df3d-eae6-45b5-8024-1929fbc905fa: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/hasdal/bfe3df3d-eae6-45b5-8024-1929fbc905fa/resolve/main/training_args.bin
- Command line
-
hf download hf://hasdal/bfe3df3d-eae6-45b5-8024-1929fbc905fa/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hasdal/bfe3df3d-eae6-45b5-8024-1929fbc905fa/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 28f9aa347670dd6cef18fc16145459d64ffec97bd85802f83529d17a59ad902a
- Size of remote file:
- 6.78 kB
- SHA256:
- 60cec0f946509605c2267869d4cefb911981bc8618f1c413a4a930934f5e46d9
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