Instructions to use openmmlab/upernet-convnext-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openmmlab/upernet-convnext-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="openmmlab/upernet-convnext-tiny")# Load model directly from transformers import AutoImageProcessor, UperNetForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("openmmlab/upernet-convnext-tiny") model = UperNetForSemanticSegmentation.from_pretrained("openmmlab/upernet-convnext-tiny") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit ·
876ffc5
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Parent(s): 6dcf81e
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (19cd0942d2015532933d2586ac5a5ed6c08eff65)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:cd55b1d36c6602d34f8cd300d7f788ea0fa5c3ed928e9ac98f353ecb31c7fa1d
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size 241053050
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