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:
- b52c23b3a56733b72149c39874e65276045c330e2d94c55eb65fa042bdb5080c
- Size of remote file:
- 3.16 GB
- SHA256:
- 36c85056f5735b848c4c2de8081ef0800bd399b0d4cd417c0d50222c18b8aad4
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