Automatic Speech Recognition
Transformers
TensorBoard
ONNX
Safetensors
whisper
Generated from Trainer
Instructions to use veract/veract-11-biov4.en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use veract/veract-11-biov4.en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="veract/veract-11-biov4.en")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("veract/veract-11-biov4.en") model = AutoModelForSpeechSeq2Seq.from_pretrained("veract/veract-11-biov4.en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download decoder_model.onnx from veract/veract-11-biov4.en: direct link, hf CLI and curl.
- Browser
- Download file 118 MB
-
https://huggingface.co/veract/veract-11-biov4.en/resolve/main/decoder_model.onnx
- Command line
-
hf download hf://veract/veract-11-biov4.en/decoder_model.onnx
-
curl -L -o decoder_model.onnx https://huggingface.co/veract/veract-11-biov4.en/resolve/main/decoder_model.onnx
118 MB
- Xet hash:
- 821ca489f84b7ce3cd32ccf5ea6487d170480154fa3fe9de11ff2a89bf6c27c4
- Size of remote file:
- 118 MB
- SHA256:
- 17affc3e5300228400d04819ae4c30cf813c5bfc7961f6a1c4939528b3b3ab69
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