Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
wav2vec2-bert
Generated from Trainer
Eval Results (legacy)
Instructions to use web2savar/mactest2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use web2savar/mactest2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="web2savar/mactest2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("web2savar/mactest2") model = AutoModelForCTC.from_pretrained("web2savar/mactest2") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer
Browse files- tokenizer_config.json +0 -1
tokenizer_config.json
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"eos_token": "</s>",
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "[PAD]",
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"processor_class": "Wav2Vec2BertProcessor",
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"replace_word_delimiter_char": " ",
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"target_lang": null,
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"tokenizer_class": "Wav2Vec2CTCTokenizer",
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"eos_token": "</s>",
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "[PAD]",
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"replace_word_delimiter_char": " ",
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"target_lang": null,
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"tokenizer_class": "Wav2Vec2CTCTokenizer",
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