Instructions to use deepmind/vision-perceiver-learned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepmind/vision-perceiver-learned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="deepmind/vision-perceiver-learned") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoTokenizer, AutoModelForImageClassification tokenizer = AutoTokenizer.from_pretrained("deepmind/vision-perceiver-learned") model = AutoModelForImageClassification.from_pretrained("deepmind/vision-perceiver-learned") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c2db976fb6a95a33fe0dd90ddfb670f6bf5ce7f228e459c33a80d244f1c33038
- Size of remote file:
- 249 MB
- SHA256:
- 8c70524d5ed3b922f125b9bd84515a3190aa6e284da84009253917640a7acc1e
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