Instructions to use Afzalsiiit/SwimV2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Afzalsiiit/SwimV2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Afzalsiiit/SwimV2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Afzalsiiit/SwimV2") model = AutoModelForImageClassification.from_pretrained("Afzalsiiit/SwimV2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7250d788798284ed9b8d6c350d5c862f690d431d0135c128284f3aeab0137e0
- Size of remote file:
- 5.14 kB
- SHA256:
- a66f4c940bf3e4b3515e03f96f1d192cf83286a0d16e5e75a8a02b5a015b125a
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