Instructions to use spicecloud/spice-mnist with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use spicecloud/spice-mnist with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="spicecloud/spice-mnist", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("spicecloud/spice-mnist", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#3
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:d8a267dc18f38e99227ebad39a52a8afcf47b92a835d0d114dbcce98d01d6a52
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size 397560
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