Instructions to use Dev372/HarshDev-whisper-tiny-English_4000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dev372/HarshDev-whisper-tiny-English_4000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Dev372/HarshDev-whisper-tiny-English_4000")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Dev372/HarshDev-whisper-tiny-English_4000") model = AutoModelForSpeechSeq2Seq.from_pretrained("Dev372/HarshDev-whisper-tiny-English_4000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer.json
Browse filesAdded Tokeniser.json file
- tokenizer.json +0 -0
tokenizer.json
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