Instructions to use peter881122/ocean2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peter881122/ocean2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="peter881122/ocean2")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("peter881122/ocean2") model = AutoModelForObjectDetection.from_pretrained("peter881122/ocean2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from peter881122/ocean2: direct link, hf CLI and curl.
- Browser
- Download file 243 MB
-
https://huggingface.co/peter881122/ocean2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://peter881122/ocean2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/peter881122/ocean2/resolve/main/pytorch_model.bin
243 MB
- Xet hash:
- 60faa59a91b406a844226d499afc54c5fb40ad227eadb11d2a5e4cace92bec2d
- Size of remote file:
- 243 MB
- SHA256:
- a347a66e30c363acbe739c18104f6f4e25d77233e39ba5b48977043d1f1fac19
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