Instructions to use EducativeCS2023/whisper-en-tiny-trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EducativeCS2023/whisper-en-tiny-trained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="EducativeCS2023/whisper-en-tiny-trained")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("EducativeCS2023/whisper-en-tiny-trained") model = AutoModelForSpeechSeq2Seq.from_pretrained("EducativeCS2023/whisper-en-tiny-trained") - Notebooks
- Google Colab
- Kaggle
Commit ·
2c9a190
1
Parent(s): c32c2b3
Training in progress, step 120
Browse files
runs/Jun15_11-47-38_educative/events.out.tfevents.1686829666.educative.155.0
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