Instructions to use basilkr/Malasar_48WER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use basilkr/Malasar_48WER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="basilkr/Malasar_48WER")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("basilkr/Malasar_48WER") model = AutoModelForSpeechSeq2Seq.from_pretrained("basilkr/Malasar_48WER") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a38e3707931059fb8a09240b9046f5cf8e258919b04a8e0debfd210bc60b7e5
- Size of remote file:
- 12.3 GB
- SHA256:
- 4ff42959dee6caf83c6648457bce0d0522921c06b0ee6d940c76e0fa1d0073c6
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