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README.md
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@@ -3,9 +3,12 @@ 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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candidate_labels: playing music, playing sports
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example_title: Cat & Dog
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---
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# SigLIP (shape-optimized model)
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@@ -37,8 +40,8 @@ import requests
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from transformers import AutoProcessor, AutoModel
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import torch
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model = AutoModel.from_pretrained("
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processor = AutoProcessor.from_pretrained("
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url = "http://images.cocodataset.org/val2017/000000039769.jpg"
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image = Image.open(requests.get(url, stream=True).raw)
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@@ -62,7 +65,7 @@ from PIL import Image
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import requests
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# load pipe
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image_classifier = pipeline(task="zero-shot-image-classification", model="
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# load image
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url = 'http://images.cocodataset.org/val2017/000000039769.jpg'
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@@ -109,4 +112,4 @@ alt="drawing" width="600"/>
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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}
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```
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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/mishig/sample_images/resolve/main/cat-dog-music.png
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candidate_labels: playing music, playing sports
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example_title: Cat & Dog
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pipeline_tag: zero-shot-image-classification
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library_name: transformers
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---
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# SigLIP (shape-optimized model)
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from transformers import AutoProcessor, AutoModel
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import torch
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model = AutoModel.from_pretrained("google/siglip-so400m-patch16-256-i18n")
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processor = AutoProcessor.from_pretrained("google/siglip-so400m-patch16-256-i18n")
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url = "http://images.cocodataset.org/val2017/000000039769.jpg"
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image = Image.open(requests.get(url, stream=True).raw)
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import requests
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# load pipe
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image_classifier = pipeline(task="zero-shot-image-classification", model="google/siglip-so400m-patch16-256-i18n")
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# load image
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url = 'http://images.cocodataset.org/val2017/000000039769.jpg'
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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}
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```
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