Zero-Shot Image Classification
Transformers
Safetensors
siglip
vision
Inference Endpoints

Set pipeline tag to image-to-text and add project page link

#2
by nielsr HF staff - opened
Files changed (1) hide show
  1. README.md +8 -7
README.md CHANGED
@@ -1,14 +1,13 @@
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  ---
 
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  license: apache-2.0
 
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  tags:
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  - vision
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  widget:
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- - src: >-
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- https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/bee.jpg
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- candidate_labels: bee in the sky, bee on the flower
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- example_title: Bee
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- library_name: transformers
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- pipeline_tag: zero-shot-image-classification
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  ---
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  # SigLIP 2 Base
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  [SigLIP](https://huggingface.co/papers/2303.15343) with prior, independently developed techniques
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  into a unified recipe, for improved semantic understanding, localization, and dense features.
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  ## Intended uses
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  You can use the raw model for tasks like zero-shot image classification and
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  primaryClass={cs.CV},
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  url={https://arxiv.org/abs/2502.14786},
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  }
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- ```
 
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  ---
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+ library_name: transformers
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  license: apache-2.0
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+ pipeline_tag: image-to-text
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  tags:
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  - vision
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  widget:
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+ - src: https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/bee.jpg
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+ candidate_labels: bee in the sky, bee on the flower
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+ example_title: Bee
 
 
 
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  ---
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  # SigLIP 2 Base
 
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  [SigLIP](https://huggingface.co/papers/2303.15343) with prior, independently developed techniques
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  into a unified recipe, for improved semantic understanding, localization, and dense features.
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+ Project page: [https://github.com/google-research/big_vision](https://github.com/google-research/big_vision)
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+
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  ## Intended uses
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  You can use the raw model for tasks like zero-shot image classification and
 
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  primaryClass={cs.CV},
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  url={https://arxiv.org/abs/2502.14786},
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  }
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+ ```