Instructions to use esc-benchmark/wav2vec2-aed-tedlium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use esc-benchmark/wav2vec2-aed-tedlium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="esc-benchmark/wav2vec2-aed-tedlium")# Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("esc-benchmark/wav2vec2-aed-tedlium") model = AutoModelForSpeechSeq2Seq.from_pretrained("esc-benchmark/wav2vec2-aed-tedlium") - Notebooks
- Google Colab
- Kaggle
File size: 135 Bytes
c594220 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:4dff7590ad263bc52a238d3c7b2d76cb572915f2f12deb3ee64046fdd196b438
size 2353616717
|