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 training_args.bin from Satish678/UIED: direct link, hf CLI and curl.
- Browser
- Download file 3.9 kB
-
https://huggingface.co/Satish678/UIED/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://Satish678/UIED@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Satish678/UIED/resolve/refs%2Fpr%2F1/training_args.bin
3.9 kB
- Xet hash:
- c7cbf2db853c7941787681028813e203441d123d98ca685760456d3dfab7c551
- Size of remote file:
- 3.9 kB
- SHA256:
- c66902488eafe52df528a285146cd86d7acbd672efb5d3d29ff99bf0cf462cd8
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