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:
# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-DPTForSemanticSegmentation: direct link, hf CLI and curl.
- Browser
- Download file 79.7 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-DPTForSemanticSegmentation/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-DPTForSemanticSegmentation@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-DPTForSemanticSegmentation/resolve/refs%2Fpr%2F1/model.safetensors
79.7 MB
- Xet hash:
- e90828eb4c1376736aa901f9cfd1b381dffded8cd74960c382d2b422464b36a2
- Size of remote file:
- 79.7 MB
- SHA256:
- 4cc5be3eb373dcd2785011fdf84c1cce2bac4d36728821d76b00233ed704e02b
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