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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
3.36 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 14 commits
anzorq
Upload lm-boosted decoder
bb1e90f about 2 years ago
  • language_model
    Upload lm-boosted decoder about 2 years ago
  • .gitattributes
    1.58 kB
    Upload lm-boosted decoder about 2 years ago
  • README.md
    3.59 kB
    Update README.md about 2 years ago
  • added_tokens.json
    30 Bytes
    Upload tokenizer about 2 years ago
  • alphabet.json
    488 Bytes
    Upload lm-boosted decoder about 2 years ago
  • config.json
    1.9 kB
    step 4000 model about 2 years ago
  • model.safetensors
    2.42 GB
    xet
    step 4000 model about 2 years ago
  • preprocessor_config.json
    279 Bytes
    Upload lm-boosted decoder about 2 years ago
  • special_tokens_map.json
    548 Bytes
    Upload tokenizer about 2 years ago
  • tokenizer_config.json
    1.1 kB
    Upload lm-boosted decoder about 2 years ago
  • training_args.bin
    4.92 kB
    xet
    Training in progress, step 1000 about 2 years ago
  • vocab.json
    560 Bytes
    Upload tokenizer about 2 years ago