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sulaimank
/
w2vbert-lingala-sd

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

Instructions to use sulaimank/w2vbert-lingala-sd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use sulaimank/w2vbert-lingala-sd with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="sulaimank/w2vbert-lingala-sd")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("sulaimank/w2vbert-lingala-sd")
    model = AutoModelForCTC.from_pretrained("sulaimank/w2vbert-lingala-sd", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle

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  • .gitattributes
    1.52 kB
    initial commit about 15 hours ago
  • README.md
    5.17 kB
    Upload processor about 15 hours ago
  • added_tokens.json
    30 Bytes
    Upload processor about 15 hours ago
  • config.json
    1.89 kB
    Training in progress, step 200 about 15 hours ago
  • model.safetensors
    2.42 GB
    xet
    Training in progress, step 5600 about 6 hours ago
  • preprocessor_config.json
    229 Bytes
    Training in progress, step 200 about 15 hours ago
  • processor_config.json
    320 Bytes
    Upload processor about 15 hours ago
  • tokenizer_config.json
    1.25 kB
    Upload processor about 15 hours ago
  • training_args.bin
    5.33 kB
    xet
    Training in progress, step 200 about 15 hours ago
  • vocab.json
    1.11 kB
    Upload processor about 15 hours ago