Instructions to use HuggingAnalist/mms-1b-asr-sna with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HuggingAnalist/mms-1b-asr-sna with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="HuggingAnalist/mms-1b-asr-sna")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("HuggingAnalist/mms-1b-asr-sna") model = AutoModelForCTC.from_pretrained("HuggingAnalist/mms-1b-asr-sna") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1479f36c403265a21d802d105bbcf97812c2b6217b5723be646dbc969867ba74
- Size of remote file:
- 5.14 kB
- SHA256:
- fb9fc70ce576e2647e176f06d80a94799763b2314dde7e7f2533e10c4efc42a4
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