wav2vec2-large-xlsr-mvc-swahili
This model is a finetuned version of facebook/wav2vec2-large-xlsr-53.
How to use the model
There was an issue with vocab, seems like there are special characters included and they were not considered during training
You could try
from transformers import AutoProcessor, AutoModelForCTC
repo_name = "eddiegulay/wav2vec2-large-xlsr-mvc-swahili"
processor = AutoProcessor.from_pretrained(repo_name)
model = AutoModelForCTC.from_pretrained(repo_name)
# if you have GPU
# move model to CUDA
model = model.to("cuda")
def transcribe(audio_path):
# Load the audio file
audio_input, sample_rate = torchaudio.load(audio_path)
target_sample_rate = 16000
audio_input = torchaudio.transforms.Resample(orig_freq=sample_rate, new_freq=target_sample_rate)(audio_input)
# Preprocess the audio data
input_dict = processor(audio_input[0], return_tensors="pt", padding=True, sampling_rate=16000)
# Perform inference and transcribe
logits = model(input_dict.input_values.to("cuda")).logits
pred_ids = torch.argmax(logits, dim=-1)[0]
transcription = processor.decode(pred_ids)
return transcription
transcript = transcribe('your_audio.mp3')
- Downloads last month
- 2
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for eddiegulay/wav2vec2-large-xlsr-mvc-swahili
Base model
facebook/wav2vec2-large-xlsr-53
Finetuned
this model