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IDEA-CCNL
/
Taiyi-CLIP-Roberta-102M-Chinese

Feature Extraction
Transformers
PyTorch
Safetensors
bert
text-classification
clip
zh
image-text
Model card Files Files and versions
xet
Community
4

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")
    # 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")
  • Notebooks
  • Google Colab
  • Kaggle
Taiyi-CLIP-Roberta-102M-Chinese
822 MB
Ctrl+K
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  • 7 contributors
History: 24 commits
Zimix's picture
Zimix
Update README.md
bc37cdc almost 3 years ago
  • .gitattributes
    1.23 kB
    Adding `safetensors` variant of this model (#3) about 3 years ago
  • README.md
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    Update README.md almost 3 years ago
  • config.json
    24.1 kB
    hello world almost 4 years ago
  • model.safetensors
    411 MB
    xet
    Adding `safetensors` variant of this model (#3) about 3 years ago
  • pytorch_model.bin
    411 MB
    xet
    add zero dataset and achieve better result over 3 years ago
  • special_tokens_map.json
    112 Bytes
    hello world almost 4 years ago
  • tokenizer_config.json
    531 Bytes
    hello world almost 4 years ago
  • vocab.txt
    110 kB
    hello world almost 4 years ago