Instructions to use voidful/hubert-tiny-v2-unit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidful/hubert-tiny-v2-unit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="voidful/hubert-tiny-v2-unit")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("voidful/hubert-tiny-v2-unit") model = AutoModelForCTC.from_pretrained("voidful/hubert-tiny-v2-unit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (15ba17bc902d34403e6b552046a93c0aa0387f49) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>c6bc4a4
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