Instructions to use MBZUAI/swiftformer-l3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MBZUAI/swiftformer-l3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="MBZUAI/swiftformer-l3") 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("MBZUAI/swiftformer-l3") model = AutoModelForImageClassification.from_pretrained("MBZUAI/swiftformer-l3") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:d968805fc2f3e20ca6799b8300fc0b5a1022bfc5bde068a229046676bea6bc36
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size 114116400
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