Instructions to use hf-internal-testing/tiny-random-SamModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SamModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="hf-internal-testing/tiny-random-SamModel")# Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-SamModel") model = AutoModelForMaskGeneration.from_pretrained("hf-internal-testing/tiny-random-SamModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e04c0314722ba8b096622ab5f6adad38b38f485ea615bbe60c04600c6899997
- Size of remote file:
- 558 kB
- SHA256:
- cd4ba6670147765274d85829c49505d51a3ab1a756a63e0a2d84717d5572bbbc
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