Instructions to use hf-internal-testing/tiny-random-ImageGPTForCausalImageModeling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ImageGPTForCausalImageModeling with Transformers:
# Load model directly from transformers import AutoImageProcessor, ImageGPTForCausalImageModeling processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-ImageGPTForCausalImageModeling") model = ImageGPTForCausalImageModeling.from_pretrained("hf-internal-testing/tiny-random-ImageGPTForCausalImageModeling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a7a1df3efb106fc075f8a753acb7210eb85c87e161769fc6705a6c2a10c5bf69
- Size of remote file:
- 5.66 MB
- SHA256:
- 956cf7e6d6bfeb01292b9f7f1d3d6edce130d3baf978402b627ab28b41bcbba6
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