Automatic Speech Recognition
Transformers
PyTorch
JAX
English
wav2vec2
audio
hf-asr-leaderboard
mozilla-foundation/common_voice_6_0
robust-speech-event
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use abidlabs/speech-text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abidlabs/speech-text with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="abidlabs/speech-text")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("abidlabs/speech-text") model = AutoModelForCTC.from_pretrained("abidlabs/speech-text") - Notebooks
- Google Colab
- Kaggle
- Size of remote file:
- 863 MB
- SHA256:
- 47e16abf6384ebd1b3395144330b60710dc43f3d16c4b2b4794071cd117230e5
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