Instructions to use esc-benchmark/wav2vec2-aed-pretrained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use esc-benchmark/wav2vec2-aed-pretrained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="esc-benchmark/wav2vec2-aed-pretrained")# Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("esc-benchmark/wav2vec2-aed-pretrained") model = AutoModelForSpeechSeq2Seq.from_pretrained("esc-benchmark/wav2vec2-aed-pretrained") - Notebooks
- Google Colab
- Kaggle
File size: 135 Bytes
26bce34 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:426a0c8b8f095282de9d9080d52d8d2bf0df5ff4d549023dc9583079af514fd7
size 2353616717
|