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 model.safetensors from gobk/cppe5_use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 166 MB
-
https://huggingface.co/gobk/cppe5_use_data_finetuning/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://gobk/cppe5_use_data_finetuning@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/gobk/cppe5_use_data_finetuning/resolve/refs%2Fpr%2F1/model.safetensors
166 MB
- Xet hash:
- b31e80e523ae6e9b10575501e52c7714fbc0300dd73080ffe2a240bbcebc4b03
- Size of remote file:
- 166 MB
- SHA256:
- 87f8bcb9a4f183ab2fbce28012e245ce19b16c1af92016cf2ccf239b68f3a1e0
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