Instructions to use OpenGVLab/internimage_l_22k_384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/internimage_l_22k_384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="OpenGVLab/internimage_l_22k_384", 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_l_22k_384", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45fb70adad65dc4b0e27570b54b482edd0239a9382a1b0a8679154a158047439
- Size of remote file:
- 1.05 GB
- SHA256:
- f02343007a913ce52bf845a32efb5dcdcd8f50495a764110c82ed484d420967c
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