Instructions to use IDEA-CCNL/Taiyi-CLIP-Roberta-102M-Chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IDEA-CCNL/Taiyi-CLIP-Roberta-102M-Chinese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="IDEA-CCNL/Taiyi-CLIP-Roberta-102M-Chinese")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IDEA-CCNL/Taiyi-CLIP-Roberta-102M-Chinese") model = AutoModelForSequenceClassification.from_pretrained("IDEA-CCNL/Taiyi-CLIP-Roberta-102M-Chinese", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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| Taiyi-CLIP-Roberta-102M-Chinese | Flickr30k-CNA-test | 46.32% | 74.58% | 83.44% |
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| Taiyi-CLIP-Roberta-102M-Chinese | COCO-CN-test | 47.10% | 78.53% | 87.84% |
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| Taiyi-CLIP-Roberta-102M-Chinese | wukong50k |
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# Citation
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| Taiyi-CLIP-Roberta-102M-Chinese | Flickr30k-CNA-test | 46.32% | 74.58% | 83.44% |
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| Taiyi-CLIP-Roberta-102M-Chinese | COCO-CN-test | 47.10% | 78.53% | 87.84% |
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| Taiyi-CLIP-Roberta-102M-Chinese | wukong50k | 49.18% | 81.94% | 90.27% |
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# Citation
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