Instructions to use sanchit-gandhi/large-v3-32-2-conditioned-timestamped-unshuffled-encoder-dropout with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sanchit-gandhi/large-v3-32-2-conditioned-timestamped-unshuffled-encoder-dropout with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sanchit-gandhi/large-v3-32-2-conditioned-timestamped-unshuffled-encoder-dropout")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("sanchit-gandhi/large-v3-32-2-conditioned-timestamped-unshuffled-encoder-dropout") model = AutoModelForSpeechSeq2Seq.from_pretrained("sanchit-gandhi/large-v3-32-2-conditioned-timestamped-unshuffled-encoder-dropout", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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