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ThinkingMachinesDataScience
/
Ratchada-Fang-Thon-Whisper

Automatic Speech Recognition
Transformers
Safetensors
English
Thai
whisper
finance
Model card Files Files and versions
xet
Community

Instructions to use ThinkingMachinesDataScience/Ratchada-Fang-Thon-Whisper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ThinkingMachinesDataScience/Ratchada-Fang-Thon-Whisper with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="ThinkingMachinesDataScience/Ratchada-Fang-Thon-Whisper")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("ThinkingMachinesDataScience/Ratchada-Fang-Thon-Whisper")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("ThinkingMachinesDataScience/Ratchada-Fang-Thon-Whisper")
  • Notebooks
  • Google Colab
  • Kaggle

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  • .gitattributes
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  • added_tokens.json
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  • config.json
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  • generation_config.json
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  • merges.txt
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  • normalizer.json
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  • preprocessor_config.json
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  • special_tokens_map.json
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  • tokenizer_config.json
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  • vocab.json
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