Instructions to use esc-bench/wav2vec2-aed-switchboard with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use esc-bench/wav2vec2-aed-switchboard with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="esc-bench/wav2vec2-aed-switchboard")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("esc-bench/wav2vec2-aed-switchboard") model = AutoModelForSpeechSeq2Seq.from_pretrained("esc-bench/wav2vec2-aed-switchboard", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Correct scripts
Sanchit Gandhi6c13e97
-
Correct scripts
Sanchit Gandhib34b9bb
-
Correct scripts
Sanchit Gandhi430edc1
-
Add scripts and weights
Sanchit Gandhid6fd54a -
Add scripts and weights
Sanchit Gandhi4941c0e -
Add scripts and weights
Sanchit Gandhi7acb122 -
initial commit
Sanchit Gandhi2c2ac00