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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3652bd6662a8346efa237489a1ccfe32d4a8fd3fbbfa35355841f817d6098898
- Size of remote file:
- 5.65 MB
- SHA256:
- 04b18826a0adf3ea278e40205e76557f93a7c7f31da2d754850d52d792361b29
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