Instructions to use eeeebbb2/b19f0afb-87c9-4c3a-9b22-183983e96095 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/b19f0afb-87c9-4c3a-9b22-183983e96095 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, "eeeebbb2/b19f0afb-87c9-4c3a-9b22-183983e96095") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/training_args.bin from eeeebbb2/b19f0afb-87c9-4c3a-9b22-183983e96095: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/eeeebbb2/b19f0afb-87c9-4c3a-9b22-183983e96095/resolve/main/last-checkpoint/training_args.bin
- Command line
-
hf download hf://eeeebbb2/b19f0afb-87c9-4c3a-9b22-183983e96095/last-checkpoint/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/eeeebbb2/b19f0afb-87c9-4c3a-9b22-183983e96095/resolve/main/last-checkpoint/training_args.bin
6.84 kB
- Xet hash:
- 05c16a78683b3920c578737f6052d73f2584aa67c63ecbae5233aa3bf1303d78
- Size of remote file:
- 6.84 kB
- SHA256:
- 9f8c8de4d939979ca4c9576ccc1432bb13cb2029566754591b76a6f783f7c5a0
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