Instructions to use OpenGVLab/InternViT-300M-448px with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/InternViT-300M-448px with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="OpenGVLab/InternViT-300M-448px", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenGVLab/InternViT-300M-448px", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add library name and github repo
Browse filesThis PR ensures the proper library name is recognized for your model (Transformers), and adds a link to the code repository.
README.md
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@@ -8,6 +8,7 @@ datasets:
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- conceptual_captions
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- wanng/wukong100m
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pipeline_tag: image-feature-extraction
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new_version: OpenGVLab/InternViT-300M-448px-V2_5
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---
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pages={24185--24198},
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year={2024}
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}
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```
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- conceptual_captions
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- wanng/wukong100m
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pipeline_tag: image-feature-extraction
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library_name: transformers
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new_version: OpenGVLab/InternViT-300M-448px-V2_5
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---
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pages={24185--24198},
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year={2024}
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}
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```
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