Instructions to use Akazawa/detr-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Akazawa/detr-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Akazawa/detr-test")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("Akazawa/detr-test") model = AutoModelForObjectDetection.from_pretrained("Akazawa/detr-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Akazawa/detr-test: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/Akazawa/detr-test/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Akazawa/detr-test/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Akazawa/detr-test/resolve/main/pytorch_model.bin
167 MB
- Xet hash:
- 32d90245719a8e4730adf4e69a42511ce7d6cc1c490c6fd23a7c88a41e074317
- Size of remote file:
- 167 MB
- SHA256:
- d109d216b4459d47bf068e742b52d3281dce222e6dce1c9b0dc0a72499a6165d
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