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Pectics
/
vad-macbert

Text Classification
Transformers
Safetensors
Chinese
bert
agent
nlp
chinese
sentiment-analysis
emotion
regression
vad
valence-arousal-dominance
macbert
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Pectics/vad-macbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Pectics/vad-macbert with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Pectics/vad-macbert")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Pectics/vad-macbert")
    model = AutoModelForSequenceClassification.from_pretrained("Pectics/vad-macbert")
  • Notebooks
  • Google Colab
  • Kaggle
vad-macbert
410 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 11 commits
Pectics's picture
Pectics
Metadata
c795015 3 months ago
  • .gitattributes
    92 Bytes
    Initial commit 3 months ago
  • .lfsconfig
    67 Bytes
    Added .lfsconfig 3 months ago
  • LICENSE
    1.06 kB
    Add MIT License file 3 months ago
  • README.md
    4.8 kB
    Metadata 3 months ago
  • README_zh.md
    4.16 kB
    Optimized README files 3 months ago
  • config.json
    1.01 kB
    Initial commit 3 months ago
  • model.safetensors
    409 MB
    xet
    Initial commit 3 months ago
  • special_tokens_map.json
    695 Bytes
    Initial commit 3 months ago
  • tokenizer.json
    439 kB
    Initial commit 3 months ago
  • tokenizer_config.json
    1.25 kB
    Initial commit 3 months ago
  • training_args.json
    729 Bytes
    Initial commit 3 months ago
  • vocab.txt
    110 kB
    Initial commit 3 months ago