Instructions to use garnagar/whisper-tiny-libirClean-vs-commonNative with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use garnagar/whisper-tiny-libirClean-vs-commonNative with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="garnagar/whisper-tiny-libirClean-vs-commonNative")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("garnagar/whisper-tiny-libirClean-vs-commonNative") model = AutoModelForSpeechSeq2Seq.from_pretrained("garnagar/whisper-tiny-libirClean-vs-commonNative", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 500
Browse files
pytorch_model.bin
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runs/Dec07_09-46-42_73abc972721c/events.out.tfevents.1670406681.73abc972721c.76.0
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