Instructions to use vision-tf/detr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vision-tf/detr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="vision-tf/detr")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("vision-tf/detr") model = AutoModelForObjectDetection.from_pretrained("vision-tf/detr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from vision-tf/detr: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/vision-tf/detr/resolve/main/training_args.bin
- Command line
-
hf download hf://vision-tf/detr/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/vision-tf/detr/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- cab08f7acc3085dc9b8c18453b71a24d0c136b318dd260ceb34aead71068d140
- Size of remote file:
- 4.86 kB
- SHA256:
- 127c4642ee6042a3e55dbd0bf2e94279ef050b2e79dbeca99b29a90fda220d66
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