Ahmadzei's picture
added 3 more tables for large emb model
5fa1a76
Usage Example:
thon
import torch
from scipy.io.wavfile import write
from datasets import Audio, load_dataset
from transformers import UnivNetFeatureExtractor, UnivNetModel
model_id_or_path = "dg845/univnet-dev"
model = UnivNetModel.from_pretrained(model_id_or_path)
feature_extractor = UnivNetFeatureExtractor.from_pretrained(model_id_or_path)
ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
Resample the audio to the model and feature extractor's sampling rate.