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/4e15fbe246000f49f5c944dfc96c19a3a8ffd6a1/training_args.bin
- Command line
-
hf download hf://gobk/cppe5_use_data_finetuning@4e15fbe246000f49f5c944dfc96c19a3a8ffd6a1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gobk/cppe5_use_data_finetuning/resolve/4e15fbe246000f49f5c944dfc96c19a3a8ffd6a1/training_args.bin
4.54 kB
- Xet hash:
- 12100a0545dd99f148aa71062e8e3505336a161ac7b83e2895b5f8efd78e161d
- Size of remote file:
- 4.54 kB
- SHA256:
- 7ebb224cb2479401d27cfebc0f7ddfaec394e837dcb1e1f7eee3481cdf628e82
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