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 pytorch_model.bin from gobk/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/gobk/cppe5_use_data_finetuning/resolve/374dfd97d35532543ede65bd38d86e643e336ab0/pytorch_model.bin
- Command line
-
hf download hf://gobk/cppe5_use_data_finetuning@374dfd97d35532543ede65bd38d86e643e336ab0/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gobk/cppe5_use_data_finetuning/resolve/374dfd97d35532543ede65bd38d86e643e336ab0/pytorch_model.bin
167 MB
- Xet hash:
- 8a4efe0e6e29d30fa410ff60ed4b12c3ef6d65b15942909d7f014c220c320079
- Size of remote file:
- 167 MB
- SHA256:
- 5b07ea86c1c02d032898603a37fb232d23798f280b76cbd153b497a16f590a76
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