Instructions to use gobk/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gobk/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="gobk/cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("gobk/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("gobk/cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gobk/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/gobk/cppe5_use_data_finetuning/resolve/main/training_args.bin
- Command line
-
hf download hf://gobk/cppe5_use_data_finetuning/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gobk/cppe5_use_data_finetuning/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 2ccfc55e6aef4371e65d6d801d75851f91f0e420664c0feb52c343dad8301286
- Size of remote file:
- 4.54 kB
- SHA256:
- c2a3b97f9c09866aaedcd8f4fd56267a2e52993be514af38716b21ff4501b0c8
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