Instructions to use Subhadeep/whisper-tiny-fet-small-model-Hi-Bank_v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Subhadeep/whisper-tiny-fet-small-model-Hi-Bank_v5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Subhadeep/whisper-tiny-fet-small-model-Hi-Bank_v5")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Subhadeep/whisper-tiny-fet-small-model-Hi-Bank_v5") model = AutoModelForSpeechSeq2Seq.from_pretrained("Subhadeep/whisper-tiny-fet-small-model-Hi-Bank_v5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 4000
Browse files
pytorch_model.bin
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runs/Dec23_05-06-13_e2e-102-206/events.out.tfevents.1671771994.e2e-102-206
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