Instructions to use Eimhin03/output_model_whisper_base_shunya_ideal_data_augmentation_enabled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Eimhin03/output_model_whisper_base_shunya_ideal_data_augmentation_enabled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Eimhin03/output_model_whisper_base_shunya_ideal_data_augmentation_enabled")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Eimhin03/output_model_whisper_base_shunya_ideal_data_augmentation_enabled") model = AutoModelForSpeechSeq2Seq.from_pretrained("Eimhin03/output_model_whisper_base_shunya_ideal_data_augmentation_enabled") - Notebooks
- Google Colab
- Kaggle