Instructions to use peter881122/oceanff with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peter881122/oceanff with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="peter881122/oceanff")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("peter881122/oceanff") model = AutoModelForObjectDetection.from_pretrained("peter881122/oceanff", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from peter881122/oceanff: direct link, hf CLI and curl.
- Browser
- Download file 26 MB
-
https://huggingface.co/peter881122/oceanff/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://peter881122/oceanff/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/peter881122/oceanff/resolve/main/pytorch_model.bin
26 MB
- Xet hash:
- d942428c8c795ea0e3b615e77e99735a09ef6ef145131fe6cc08899c24014683
- Size of remote file:
- 26 MB
- SHA256:
- e298388c98594a306142404fd81346abf302e976a989d6fdadf52b115d3af955
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