Instructions to use slplab/whisper-large_v2-asd_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use slplab/whisper-large_v2-asd_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="slplab/whisper-large_v2-asd_v1")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("slplab/whisper-large_v2-asd_v1") model = AutoModelForSpeechSeq2Seq.from_pretrained("slplab/whisper-large_v2-asd_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2 opened over 1 year ago
by
SFconvertbot
Librarian Bot: Add base_model information to model
#1 opened almost 3 years ago
by
librarian-bot