Instructions to use hf-internal-testing/tiny-random-Mask2FormerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Mask2FormerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-Mask2FormerModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-Mask2FormerModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-Mask2FormerModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-Mask2FormerModel: direct link, hf CLI and curl.
- Browser
- Download file 47.3 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-Mask2FormerModel/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-Mask2FormerModel@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-Mask2FormerModel/resolve/refs%2Fpr%2F1/model.safetensors
47.3 MB
- Xet hash:
- 87106739b3df803878bf3a6b909d7b05d05aed726572c23fcaaf1c877c4643e7
- Size of remote file:
- 47.3 MB
- SHA256:
- 1e84295afd0a89bf3e56fc5673975950a019c32d5c59e7198a78f76559b3f285
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