Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
speech-encoder-decoder
Generated from Trainer
Instructions to use speech-seq2seq/wav2vec2-2-bert-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use speech-seq2seq/wav2vec2-2-bert-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-bert-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("speech-seq2seq/wav2vec2-2-bert-large") model = AutoModelForSpeechSeq2Seq.from_pretrained("speech-seq2seq/wav2vec2-2-bert-large") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- Feb07_20-25-56_sanchit--v100
- Feb07_20-28-32_sanchit--v100
- Feb07_20-29-27_sanchit--v100
- Feb07_20-44-59_sanchit--v100
- Feb08_15-04-36_sanchit--v100
- Feb08_15-10-10_sanchit--v100
- Feb08_15-11-13_sanchit--v100
- Feb08_15-12-28_sanchit--v100
- Feb08_15-15-28_sanchit--v100
- Feb08_15-16-26_sanchit--v100
- Feb09_14-32-13_sanchit--v100
- Feb09_14-34-30_sanchit--v100
- Feb09_14-35-57_sanchit--v100
- Feb09_14-37-59_sanchit--v100
- Feb09_21-53-07_sanchit--v100