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")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("abidlabs/speech-text") model = AutoModelForCTC.from_pretrained("abidlabs/speech-text", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from abidlabs/speech-text: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/abidlabs/speech-text/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://abidlabs/speech-text/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/abidlabs/speech-text/resolve/main/flax_model.msgpack
1.26 GB
- Size of remote file:
- 1.26 GB
- SHA256:
- 0d3842440388a575e19f19cdb05714afd7018392bd1a7e247c601530a653aa40
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