Instructions to use dia218/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dia218/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="dia218/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("dia218/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("dia218/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dia218/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/dia218/cppe5_use_data_finetuning/resolve/0877e0b158cc55a8b5759973c00a22ee8ecdfd99/training_args.bin
- Command line
-
hf download hf://dia218/cppe5_use_data_finetuning@0877e0b158cc55a8b5759973c00a22ee8ecdfd99/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dia218/cppe5_use_data_finetuning/resolve/0877e0b158cc55a8b5759973c00a22ee8ecdfd99/training_args.bin
4.54 kB
- Xet hash:
- 14d695eb1ed70a4f7d7dd0f150190241516cc71d8bb5e5ba253547ffcfd10649
- Size of remote file:
- 4.54 kB
- SHA256:
- 3ae63f65addcf3719d6120e2db407e4ffa9002df50eddbe88af72079363e9bd3
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