Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
speech-encoder-decoder
Generated from Trainer
Instructions to use speech-seq2seq/wav2vec2-2-roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use speech-seq2seq/wav2vec2-2-roberta-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="speech-seq2seq/wav2vec2-2-roberta-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("speech-seq2seq/wav2vec2-2-roberta-large") model = AutoModelForSpeechSeq2Seq.from_pretrained("speech-seq2seq/wav2vec2-2-roberta-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fcb285e8558eca56bc0b9cba6891aa136b6a9cb22fb1427ff26877e2ee075cc0
- Size of remote file:
- 3.12 kB
- SHA256:
- 2776142faecac61f1ad96b9cb6ea226dcf4159beb1ddd83f3d447a162af69fa4
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