Instructions to use peter881122/ocean52 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peter881122/ocean52 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="peter881122/ocean52")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("peter881122/ocean52") model = AutoModelForObjectDetection.from_pretrained("peter881122/ocean52", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from peter881122/ocean52: direct link, hf CLI and curl.
- Browser
- Download file 26 MB
-
https://huggingface.co/peter881122/ocean52/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://peter881122/ocean52/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/peter881122/ocean52/resolve/main/pytorch_model.bin
26 MB
- Xet hash:
- 349c87abd0eb2d2196d9ff580d43a5816aa78aba7d91a403d7aa0234b67cc965
- Size of remote file:
- 26 MB
- SHA256:
- ab504ac3b05415ea920b07abb59a54df62c796c62e2eded3cc649d9f85d7904d
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