Instructions to use voidful/hubert-tiny-v2-unit-beamnorm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidful/hubert-tiny-v2-unit-beamnorm 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-beamnorm")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("voidful/hubert-tiny-v2-unit-beamnorm") model = AutoModelForCTC.from_pretrained("voidful/hubert-tiny-v2-unit-beamnorm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
3241027 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:903c18d6d8b9be1c4948618e8be9fdf0211890dcb1a90ea48ee9ac1648327fe4
size 103057823
|