Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
English
wav2vec2
phoneme-recognition
Generated from Trainer
Eval Results (legacy)
Instructions to use bookbot/wav2vec2-ljspeech-gruut with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bookbot/wav2vec2-ljspeech-gruut with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bookbot/wav2vec2-ljspeech-gruut")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("bookbot/wav2vec2-ljspeech-gruut") model = AutoModelForCTC.from_pretrained("bookbot/wav2vec2-ljspeech-gruut", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from bookbot/wav2vec2-ljspeech-gruut: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/bookbot/wav2vec2-ljspeech-gruut/resolve/a07b1bf4fcc7d5091a8c4b673efcb2df2c3a99ae/pytorch_model.bin
- Command line
-
hf download hf://bookbot/wav2vec2-ljspeech-gruut@a07b1bf4fcc7d5091a8c4b673efcb2df2c3a99ae/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/bookbot/wav2vec2-ljspeech-gruut/resolve/a07b1bf4fcc7d5091a8c4b673efcb2df2c3a99ae/pytorch_model.bin
378 MB
- Xet hash:
- 2cf5c5064f19ca801e100a835a5a585a2024777eb7eb00f2d20ac040e16da4b6
- Size of remote file:
- 378 MB
- SHA256:
- 6700beb43261b0090c4ab5834ca87fe488242f6351d666e912af4a2cd8025314
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