Instructions to use RISys-Lab/ReasonCLIP-B32-S0-Des with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RISys-Lab/ReasonCLIP-B32-S0-Des with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="RISys-Lab/ReasonCLIP-B32-S0-Des") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("RISys-Lab/ReasonCLIP-B32-S0-Des") model = AutoModelForZeroShotImageClassification.from_pretrained("RISys-Lab/ReasonCLIP-B32-S0-Des", device_map="auto") - Notebooks
- Google Colab
- Kaggle
docs: add playground link
Browse files
README.md
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---
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library_name: transformers
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license: cc-by-nc-sa-4.0
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tags: []
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---
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## Model Details
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- Model: ReasonCLIP-B32-S0-Des
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- Base model: [openai/clip-vit-base-patch32](https://huggingface.co/openai/clip-vit-base-patch32)
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- Architecture: CLIP ViT-B/32
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- Image resolution: 224
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- Training stage: Stage 0 - Descriptive
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- Training data: [CC12M-Refined](https://huggingface.co/datasets/RISys-Lab/CC12M-Refined)
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## Method
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## Resources
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- GitHub: [RISys-Lab/ReasonCLIP](https://github.com/RISys-Lab/ReasonCLIP)
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- Paper: [arXiv:2606.26794](https://arxiv.org/abs/2606.26794)
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---
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library_name: transformers
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license: cc-by-nc-sa-4.0
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tags: []
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---
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## Model Details
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- Model: ReasonCLIP-B32-S0-Des
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- Base model: [openai/clip-vit-base-patch32](https://huggingface.co/openai/clip-vit-base-patch32)
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- Architecture: CLIP ViT-B/32
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- Image resolution: 224
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- Training stage: Stage 0 - Descriptive
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- Training data: [CC12M-Refined](https://huggingface.co/datasets/RISys-Lab/CC12M-Refined)
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## Method
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## Resources
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- GitHub: [RISys-Lab/ReasonCLIP](https://github.com/RISys-Lab/ReasonCLIP)
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- Paper: [arXiv:2606.26794](https://arxiv.org/abs/2606.26794)
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- Playground: [ReasonCLIP Playground](https://www.sczhang.com/reasonclip/)
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## Usage
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```python
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from transformers import CLIPModel, CLIPProcessor
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model_id = "RISys-Lab/ReasonCLIP-B32-S0-Des"
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model = CLIPModel.from_pretrained(model_id)
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processor = CLIPProcessor.from_pretrained(model_id)
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```
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For the full checkpoint list, see the [ReasonCLIP model card](https://github.com/RISys-Lab/ReasonCLIP/blob/main/doc/model_card.md).
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