Instructions to use Satish678/UIED with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Satish678/UIED with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Satish678/UIED")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("Satish678/UIED") model = AutoModelForObjectDetection.from_pretrained("Satish678/UIED", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Satish678/UIED: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/Satish678/UIED/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Satish678/UIED/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Satish678/UIED/resolve/main/pytorch_model.bin
167 MB
- Xet hash:
- 6a1d1770ffaefc1329a7fa460726faab21004599e37023d5c796edc4a3a81658
- Size of remote file:
- 167 MB
- SHA256:
- 7a83425d3138a2c529501181acab2a3758733a0bad9dbebd8905e6616f53527c
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