Instructions to use hf-internal-testing/tiny-random-DPTForSemanticSegmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DPTForSemanticSegmentation with Transformers:
# Load model directly from transformers import AutoImageProcessor, DPTForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-DPTForSemanticSegmentation") model = DPTForSemanticSegmentation.from_pretrained("hf-internal-testing/tiny-random-DPTForSemanticSegmentation") - 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 sha256:4cc5be3eb373dcd2785011fdf84c1cce2bac4d36728821d76b00233ed704e02b
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size 79686072
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