Instructions to use hf-internal-testing/tiny-random-MaskFormerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MaskFormerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-MaskFormerModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-MaskFormerModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-MaskFormerModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-MaskFormerModel: direct link, hf CLI and curl.
- Browser
- Download file 45.7 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-MaskFormerModel/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-MaskFormerModel@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-MaskFormerModel/resolve/refs%2Fpr%2F1/model.safetensors
45.7 MB
- Xet hash:
- ae29163389088234e98b767dc1d101948429e6f1ad69ec2c71150785acb7e2cc
- Size of remote file:
- 45.7 MB
- SHA256:
- ec81d6e52fc1f23f786343645eea1940d43c3ef840382b5cd055e64dfe5782ed
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