Instructions to use hf-tiny-model-private/tiny-random-ImageGPTModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-ImageGPTModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-tiny-model-private/tiny-random-ImageGPTModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-ImageGPTModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-ImageGPTModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9780b4a85c78e991bdac4caae673ed4d619258a3183cca86148eb35b73a2f16b
- Size of remote file:
- 5.58 MB
- SHA256:
- 2b8cfedab91cc2adf0944a51008c1f451a5c8b1e94377fd9ffeea5df45034190
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