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
| { | |
| "epoch": 3.0, | |
| "eval_loss": 12.169343948364258, | |
| "eval_runtime": 1182.8465, | |
| "eval_samples": 2642, | |
| "eval_samples_per_second": 2.234, | |
| "eval_steps_per_second": 0.28, | |
| "eval_wer": 1.0 | |
| } |