Instructions to use OpenGVLab/internimage_s_1k_224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/internimage_s_1k_224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="OpenGVLab/internimage_s_1k_224", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenGVLab/internimage_s_1k_224", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 853a648b1ec0522261e1cf213d3b4744a79392940024b6053ff6bd173d19d1cc
- Size of remote file:
- 200 MB
- SHA256:
- dc022df2714a5ec4f54571f9b92688b8828edf3a781b6d144fc6c13ab2a557f8
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