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anzorq
/
w2v-bert-2.0-kbd-v2

Automatic Speech Recognition
Transformers
Safetensors
Kabardian
wav2vec2-bert
Model card Files Files and versions
xet
Community

Instructions to use anzorq/w2v-bert-2.0-kbd-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use anzorq/w2v-bert-2.0-kbd-v2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="anzorq/w2v-bert-2.0-kbd-v2")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("anzorq/w2v-bert-2.0-kbd-v2")
    model = AutoModelForCTC.from_pretrained("anzorq/w2v-bert-2.0-kbd-v2")
  • Notebooks
  • Google Colab
  • Kaggle
w2v-bert-2.0-kbd-v2 / language_model
934 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 1 commit
anzorq
Upload lm-boosted decoder
bb1e90f about 2 years ago
  • 5gram.bin
    910 MB
    xet
    Upload lm-boosted decoder about 2 years ago
  • attrs.json
    78 Bytes
    Upload lm-boosted decoder about 2 years ago
  • unigrams.txt
    23.7 MB
    xet
    Upload lm-boosted decoder about 2 years ago