Model Card for Respeecher/ukrainian-data2vec

This model can be used as Feature Extractor model for Ukrainian language audio data

It can also be used as Backbone for downstream tasks, like ASR, Audio Classification, etc.

How to Get Started with the Model

from transformers import AutoProcessor, Data2VecAudioModel
import torch
from datasets import load_dataset, Audio

dataset = load_dataset("mozilla-foundation/common_voice_11_0", "uk", split="validation")
# Resample
dataset = dataset.cast_column("audio", Audio(sampling_rate=16_000))

processor = AutoProcessor.from_pretrained("Respeecher/ukrainian-data2vec")
model = Data2VecAudioModel.from_pretrained("Respeecher/ukrainian-data2vec")

# audio file is decoded on the fly
inputs = processor(dataset[0]["audio"]["array"], sampling_rate=sampling_rate, return_tensors="pt")
with torch.no_grad():
    outputs = model(**inputs)

last_hidden_states = outputs.last_hidden_state
list(last_hidden_states.shape)