Instructions to use slplab/whisper-large_v2_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use slplab/whisper-large_v2_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="slplab/whisper-large_v2_test")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("slplab/whisper-large_v2_test") model = AutoModelForSpeechSeq2Seq.from_pretrained("slplab/whisper-large_v2_test") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#3 opened about 1 year ago
by
SFconvertbot
Librarian Bot: Add base_model information to model
#2 opened over 2 years ago
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librarian-bot
Update handler.py
#1 opened almost 3 years ago
by
slplab