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")# Load model directly from transformers import AutoImageProcessor, AutoModelForMultimodalLM processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-MaskFormerModel") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-random-MaskFormerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d635ab2ccf71501a2e67a5e87384e0e39e6bc6a1f7241a060677332c0626d900
- Size of remote file:
- 45.8 MB
- SHA256:
- 556f67edb91094dc174d8f04679f8e5248ae7f84300dae3ea570e1feb513deb9
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