Instructions to use jungwoo3490/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jungwoo3490/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="jungwoo3490/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("jungwoo3490/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("jungwoo3490/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jungwoo3490/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/jungwoo3490/cppe5_use_data_finetuning/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://jungwoo3490/cppe5_use_data_finetuning@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jungwoo3490/cppe5_use_data_finetuning/resolve/refs%2Fpr%2F1/training_args.bin
4.54 kB
- Xet hash:
- 1dff912cd4c1a94b2f5894a6ebc7e787b2d0d355979a2cde11479afcc6db3a7b
- Size of remote file:
- 4.54 kB
- SHA256:
- 5074946bc6d90e56ad809cd56eb9881de596e622602f2c35cd32d14baf81a606
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