Instructions to use shunk031/aesthetics-predictor-v1-vit-base-patch16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shunk031/aesthetics-predictor-v1-vit-base-patch16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="shunk031/aesthetics-predictor-v1-vit-base-patch16", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("shunk031/aesthetics-predictor-v1-vit-base-patch16", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
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:ef7094efba34c272706d3e4e3736aa9099c8ff03ab4f894e621cc95b2f6348a0
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size 344798348
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