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bharatddd
/
Whisper-Marathi-Finetuned

Automatic Speech Recognition
Transformers
Safetensors
Marathi
whisper
ASR
Whisper
speech
recognition
speech_recognition
Model card Files Files and versions
xet
Community

Instructions to use bharatddd/Whisper-Marathi-Finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use bharatddd/Whisper-Marathi-Finetuned with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="bharatddd/Whisper-Marathi-Finetuned")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("bharatddd/Whisper-Marathi-Finetuned")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("bharatddd/Whisper-Marathi-Finetuned")
  • Notebooks
  • Google Colab
  • Kaggle
Whisper-Marathi-Finetuned
969 MB
Ctrl+K
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  • 1 contributor
History: 3 commits
bharatddd's picture
bharatddd
Create README.md
67aca31 verified 4 months ago
  • .gitattributes
    1.52 kB
    initial commit 4 months ago
  • README.md
    287 Bytes
    Create README.md 4 months ago
  • added_tokens.json
    34.6 kB
    Upload folder using huggingface_hub 4 months ago
  • config.json
    1.42 kB
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  • generation_config.json
    3.86 kB
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  • merges.txt
    494 kB
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  • model.safetensors
    967 MB
    xet
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  • normalizer.json
    52.7 kB
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  • preprocessor_config.json
    339 Bytes
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  • special_tokens_map.json
    2.19 kB
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  • tokenizer_config.json
    283 kB
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  • vocab.json
    1.04 MB
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