Instructions to use eeeebbb2/2d0d5973-48d1-4d92-abc3-ec4e8f163f0b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/2d0d5973-48d1-4d92-abc3-ec4e8f163f0b 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, "eeeebbb2/2d0d5973-48d1-4d92-abc3-ec4e8f163f0b") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from eeeebbb2/2d0d5973-48d1-4d92-abc3-ec4e8f163f0b: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/eeeebbb2/2d0d5973-48d1-4d92-abc3-ec4e8f163f0b/resolve/main/training_args.bin
- Command line
-
hf download hf://eeeebbb2/2d0d5973-48d1-4d92-abc3-ec4e8f163f0b/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/eeeebbb2/2d0d5973-48d1-4d92-abc3-ec4e8f163f0b/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 7cc22754cfe580e563c10652f4ebc41e006b5b960b37a339d10839f764b31be0
- Size of remote file:
- 6.84 kB
- SHA256:
- b2ecda8520aa78b457d2646d3d5ae5ffbfea097fe1069ca6706915b57973421e
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