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/309695ebf72bc4e111420deec6bcd15d833bc0d6/pytorch_model.bin
- Command line
-
hf download hf://gobk/cppe5_use_data_finetuning@309695ebf72bc4e111420deec6bcd15d833bc0d6/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gobk/cppe5_use_data_finetuning/resolve/309695ebf72bc4e111420deec6bcd15d833bc0d6/pytorch_model.bin
167 MB
- Xet hash:
- 640101a1e252bc732a2ebc9456aaca30c86f8db25c4c2bec847ebb27137e603a
- Size of remote file:
- 167 MB
- SHA256:
- 89d702a2f047cd9d15bd97ef192f3789fb84080998d59b8cec60ca9f7575b913
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