Instructions to use charris/hubert_vanilla_527_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use charris/hubert_vanilla_527_4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="charris/hubert_vanilla_527_4")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("charris/hubert_vanilla_527_4") model = AutoModelForCTC.from_pretrained("charris/hubert_vanilla_527_4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1251627f3e261f96f2db6471df810a46838f2cbd6142ae55bd02c7f7a19950ba
- Size of remote file:
- 5.11 kB
- SHA256:
- c1cee0d25ef26ee7252812fc66dd2d9f68544f182282311849acd8e3bbb7b88f
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