Instructions to use Injardav/detr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Injardav/detr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Injardav/detr")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("Injardav/detr") model = AutoModelForObjectDetection.from_pretrained("Injardav/detr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Injardav/detr: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/Injardav/detr/resolve/main/training_args.bin
- Command line
-
hf download hf://Injardav/detr/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Injardav/detr/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- 7ca0e625185cc2a0f556323a2fc41e3864c4300d7f913dfe24da8942f5af2df1
- Size of remote file:
- 4.86 kB
- SHA256:
- 65569e5826131d73287b95e1fa5b3decaf8b95bd891e627742fc3dae686ccb60
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