Instructions to use facebook/data2vec-vision-large-ft1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/data2vec-vision-large-ft1k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/data2vec-vision-large-ft1k") 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("facebook/data2vec-vision-large-ft1k") model = AutoModelForImageClassification.from_pretrained("facebook/data2vec-vision-large-ft1k") - Notebooks
- Google Colab
- Kaggle
Add TensorFlow weights
Browse files- tf_model.h5 +3 -0
tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:df7a57f7c45b592a557becbde11b97a8ea9dec9a1c72be863132c380a5271e6c
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size 1218306616
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