Instructions to use Leonnorblad/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Leonnorblad/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Leonnorblad/test")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("Leonnorblad/test") model = AutoModelForObjectDetection.from_pretrained("Leonnorblad/test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Leonnorblad/test: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/Leonnorblad/test/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Leonnorblad/test/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Leonnorblad/test/resolve/main/pytorch_model.bin
167 MB
- Xet hash:
- 9dfa6dc11c30ea823d9ba3ac45307e4f801239dd29c2c2193a2de66f6a2ac6da
- Size of remote file:
- 167 MB
- SHA256:
- 48a7ff37dea9b114b35582ec580a3a98da75bb040de9d03dfdf9ee82a222ed8f
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