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README.md
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README.md
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@ -2,16 +2,22 @@
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tags:
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- vision
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widget:
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- src: feastival.jpg
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candidate_labels: 灯笼, 对联, 年糕, 鞭炮
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- src: https://huggingface.co/OFA-Sys/chinese-clip-vit-base-patch16/resolve/main/festival.jpg
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candidate_labels: 灯笼, 鞭炮, 对联
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example_title: festival
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/cat-dog-music.png
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candidate_labels: 音乐表演, 体育运动
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example_title: cat & dog
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/football-match.jpg
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candidate_labels: 梅西, C罗, 马奎尔
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example_title: football
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---
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# Chinese-CLIP-ViT-Base-Patch16
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## Introduction
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This is the base-version of the Chinese CLIP, with ViT-B/16 as the image encoder and RoBERTa-wwm-base as the text encoder. Chinese CLIP is a simple implementation of CLIP on a large-scale dataset of around 200 million Chinese image-text pairs. For more details, please refer to our technical report https://arxiv.org/abs/2211.01335 and our official github repo https://github.com/OFA-Sys/Chinese-CLIP
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This is the base-version of the Chinese CLIP, with ViT-B/16 as the image encoder and RoBERTa-wwm-base as the text encoder. Chinese CLIP is a simple implementation of CLIP on a large-scale dataset of around 200 million Chinese image-text pairs. For more details, please refer to our technical report https://arxiv.org/abs/2211.01335 and our official github repo https://github.com/OFA-Sys/Chinese-CLIP (Welcome to star! 🔥🔥)
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## Use with the official API
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We provide a simple code snippet to show how to use the API of Chinese-CLIP to compute the image & text embeddings and similarities.
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