 Evaluation  The model can be evaluated as follows on the Portuguese test data of Common Voice.  You need to install Enelvo, an open-source spell correction trained with Twitter user posts `pip install enelvo`  ```python import torch import torchaudio from datasets import load_dataset, load_metric from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor from enelvo import normaliser import re  test_dataset = load_dataset("common_voice", "pt", split="test") wer = load_metric("wer")  processor = Wav2Vec2Processor.from_pretrained("joorock12/wav2vec2-large-100k-voxpopuli-pt") model = Wav2Vec2ForCTC.from_pretrained("joorock12/wav2vec2-large-100k-voxpopuli-pt") model.to("cuda")  chars_to_ignore_regex = '[\,\?\.\!\-\;\:\"\“\%\‘\”\�]' resampler = torchaudio.transforms.Resample(48_000, 16_000) norm = normaliser.Normaliser()  