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:
- 10ad126e5f6693c9cde5c39f2cd4cc73124199ea0cd1cd2767ac012ef5ce7047
- Size of remote file:
- 5.59 MB
- SHA256:
- b6c32bff2eac8b584d3379d126105acc27faacb39e4412362633d6c284c2d052
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