Datasetpublic

zuhri025/Urdu_munch-MyLina

from datasets import load_dataset from linacodec.codec import LinaCodec from IPython.display import Audio import torch from datasets import load_dataset ds = load_dataset("zuhri025/Urdu_munch-MyLina", split="train") print(ds) print(ds.column_names) Pick a sample sample = ds[0] Device device = "cuda" if torch.cuda.is_available() else "cpu" Convert to tensors and move to device speech_tokens = torch.tensor(sample["speech_tokens"]).to(device)… See the full description on the dataset page: https://huggingface.co/datasets/zuhri025/Urdu_munch-MyLina.

sourceHugging Faceupdated 9mo agoView on Hugging Face

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Dataset Card

from datasets import load_dataset from linacodec.codec import LinaCodec from IPython.display import Audio import torch

from datasets import load_dataset

ds = loaddataset("zuhri025/Urdumunch-MyLina", split="train") print(ds) print(ds.column_names)

Pick a sample

sample = ds[0]

Device

device = "cuda" if torch.cuda.is_available() else "cpu"

Convert to tensors and move to device

speechtokens = torch.tensor(sample["speechtokens"]).to(device) globalembedding = torch.tensor(sample["globalembedding"]).to(device)

Decode

linatokenizer = LinaCodec() audioout = linatokenizer.decode(speechtokens, global_embedding)

Move to CPU before using NumPy / IPython Audio

audiooutcpu = audio_out.cpu().numpy()

Play

Audio(audiooutcpu, rate=48000)