Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
speech-encoder-decoder
librispeech_asr
Generated from Trainer
asr_seq2esq
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
- Xet hash:
- be68cf3f104acba2f59c33d46955d9c638ce2a5c3ac0bc0c2c5150ee6fff4a96
- Size of remote file:
- 3.06 kB
- SHA256:
- c029da8afe9a48537ce0d99ab7e8b3fe26f7bf6fda6f49c143ff0da9917a35f4
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