Instructions to use SvNext/GambleTestDETR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SvNext/GambleTestDETR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="SvNext/GambleTestDETR")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("SvNext/GambleTestDETR") model = AutoModelForObjectDetection.from_pretrained("SvNext/GambleTestDETR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SvNext/GambleTestDETR: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/SvNext/GambleTestDETR/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SvNext/GambleTestDETR/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SvNext/GambleTestDETR/resolve/main/pytorch_model.bin
167 MB
- Xet hash:
- 4934090aa2fc7ddbb356610569fe08454df65a5783dfaa613ee2e8d35b17e1fc
- Size of remote file:
- 167 MB
- SHA256:
- 561d1391af897bd062f2a8c4c8e81d66e111db911df203d96a36673f6dd82547
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