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patrickvonplaten
/
wav2vec2-2-bart-base

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
speech-encoder-decoder
librispeech_asr
Generated from Trainer
asr_seq2esq
Model card Files Files and versions
xet
Metrics Training metrics Community
3

Instructions to use patrickvonplaten/wav2vec2-2-bart-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use patrickvonplaten/wav2vec2-2-bart-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="patrickvonplaten/wav2vec2-2-bart-base")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq
    
    tokenizer = AutoTokenizer.from_pretrained("patrickvonplaten/wav2vec2-2-bart-base")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("patrickvonplaten/wav2vec2-2-bart-base", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
wav2vec2-2-bart-base
3.02 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 11 commits
librarian-bot's picture
librarian-bot
Librarian Bot: Add base_model information to model
ca5a6e9 almost 3 years ago
  • checkpoint-2000
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  • runs
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  • .gitattributes
    1.18 kB
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  • README.md
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    Librarian Bot: Add base_model information to model almost 3 years ago
  • all_results.json
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  • config.json
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  • create_model.py
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  • emissions.csv
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  • merges.txt
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  • preprocessor_config.json
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  • pytorch_model.bin
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    xet
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  • run_librispeech.sh
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  • run_speech_recognition_seq2seq.py
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  • special_tokens_map.json
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  • tokenizer.json
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  • train_results.json
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  • training_args.bin
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  • vocab.json
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