Instructions to use prxy5608/8c5883da-03dd-40f7-b0ec-a0ad53e4b9b5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use prxy5608/8c5883da-03dd-40f7-b0ec-a0ad53e4b9b5 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("fxmarty/tiny-random-GemmaForCausalLM") model = PeftModel.from_pretrained(base_model, "prxy5608/8c5883da-03dd-40f7-b0ec-a0ad53e4b9b5") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/training_args.bin from prxy5608/8c5883da-03dd-40f7-b0ec-a0ad53e4b9b5: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/prxy5608/8c5883da-03dd-40f7-b0ec-a0ad53e4b9b5/resolve/main/last-checkpoint/training_args.bin
- Command line
-
hf download hf://prxy5608/8c5883da-03dd-40f7-b0ec-a0ad53e4b9b5/last-checkpoint/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/prxy5608/8c5883da-03dd-40f7-b0ec-a0ad53e4b9b5/resolve/main/last-checkpoint/training_args.bin
6.84 kB
- Xet hash:
- 5f4b3727f3e9808fc2451106427116bb505fffd4f74bd8f7dde8de63be95f024
- Size of remote file:
- 6.84 kB
- SHA256:
- b15b8aef97848b1070be3e09e39be2ceb9ed3d4ad8190e54b4ad849296ad3bc3
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