Instructions to use peter881122/ocean50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peter881122/ocean50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="peter881122/ocean50")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("peter881122/ocean50") model = AutoModelForObjectDetection.from_pretrained("peter881122/ocean50", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from peter881122/ocean50: direct link, hf CLI and curl.
- Browser
- Download file 26 MB
-
https://huggingface.co/peter881122/ocean50/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://peter881122/ocean50/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/peter881122/ocean50/resolve/main/pytorch_model.bin
26 MB
- Xet hash:
- a04fe635b5c45ceefba87e5dbcf80895d0895d2b589786192f0537a6b23b359e
- Size of remote file:
- 26 MB
- SHA256:
- fc36af6ecae25711ae4879d900ae7481932af9456456cfd3aec93a99c1bab625
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