Instructions to use prxy5608/b51f1ae6-21f1-4ecb-b0c2-95553d0ecf00 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use prxy5608/b51f1ae6-21f1-4ecb-b0c2-95553d0ecf00 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("fxmarty/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "prxy5608/b51f1ae6-21f1-4ecb-b0c2-95553d0ecf00") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/training_args.bin from prxy5608/b51f1ae6-21f1-4ecb-b0c2-95553d0ecf00: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/prxy5608/b51f1ae6-21f1-4ecb-b0c2-95553d0ecf00/resolve/main/last-checkpoint/training_args.bin
- Command line
-
hf download hf://prxy5608/b51f1ae6-21f1-4ecb-b0c2-95553d0ecf00/last-checkpoint/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/prxy5608/b51f1ae6-21f1-4ecb-b0c2-95553d0ecf00/resolve/main/last-checkpoint/training_args.bin
6.84 kB
- Xet hash:
- 1ed76be471b56571e6807082a9ad912bc91a65710ac21bf4c645faf9096b6968
- Size of remote file:
- 6.84 kB
- SHA256:
- a0968f9c23203b771edb9a0a357ba003065283e8d5ae6347e8bb4894972aa1f3
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