Instructions to use hf-tiny-model-private/tiny-random-DPTForSemanticSegmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-DPTForSemanticSegmentation with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, DPTForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-DPTForSemanticSegmentation") model = DPTForSemanticSegmentation.from_pretrained("hf-tiny-model-private/tiny-random-DPTForSemanticSegmentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-DPTForSemanticSegmentation: direct link, hf CLI and curl.
- Browser
- Download file 79.7 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-DPTForSemanticSegmentation/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-DPTForSemanticSegmentation@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-DPTForSemanticSegmentation/resolve/refs%2Fpr%2F1/model.safetensors
79.7 MB
- Xet hash:
- bfc256437115f2978776e0883c7106264d15eddf53194ef457246b802c3f890a
- Size of remote file:
- 79.7 MB
- SHA256:
- 8535345448f385a7be0b844e27e1b5a275da945b1eddf49c29f71dc7857c7bb9
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