Instructions to use cvm2024/detr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cvm2024/detr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="cvm2024/detr")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("cvm2024/detr") model = AutoModelForObjectDetection.from_pretrained("cvm2024/detr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from cvm2024/detr: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/cvm2024/detr/resolve/main/training_args.bin
- Command line
-
hf download hf://cvm2024/detr/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/cvm2024/detr/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- 5ad04fa85401ac97cbdff4344587460a0eba5fbc8c36ada73afde8e980a79b99
- Size of remote file:
- 4.86 kB
- SHA256:
- e7afbb93c2cc7b420cfe1035a3223e15c37eceb1e82c9de42688091e7f420a4a
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