Instructions to use EUNSEO56/use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EUNSEO56/use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="EUNSEO56/use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("EUNSEO56/use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("EUNSEO56/use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from EUNSEO56/use_data_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/EUNSEO56/use_data_finetuning/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://EUNSEO56/use_data_finetuning/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/EUNSEO56/use_data_finetuning/resolve/main/pytorch_model.bin
167 MB
- Xet hash:
- 875e238ed1785d78e6236e257ff10d4b383081967af16e1427b529927a359b09
- Size of remote file:
- 167 MB
- SHA256:
- 93007679bbb28f7602d7a8c3bed14e2e0060038ed05a29f9dd1bccbcd3ccffd6
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