Instructions to use hf-internal-testing/tiny-random-ImageGPTModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ImageGPTModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-internal-testing/tiny-random-ImageGPTModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-ImageGPTModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-ImageGPTModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 305b8f25f0ba51addc3952e58a5e750f344eec6e8f0a7ca6edf8ee99fae2ff5f
- Size of remote file:
- 5.59 MB
- SHA256:
- 63133606540f2211f8e031e184cfa29dfd87ed6283835210780e0f2622e5eb6d
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