# Load model directly
from transformers import AutoProcessor, AutoModelForCTC
processor = AutoProcessor.from_pretrained("bartelds/gos-gpu6-cp1_adp0_144m-silver_48-orig_5e-4_cp-11000")
model = AutoModelForCTC.from_pretrained("bartelds/gos-gpu6-cp1_adp0_144m-silver_48-orig_5e-4_cp-11000")Quick Links
A Gronings Wav2Vec2 model. This model is created by fine-tuning the multilingual XLS-R model that is further pre-trained on Gronings speech.
This model is part of the paper: Making More of Little Data: Improving Low-Resource Automatic Speech Recognition Using Data Augmentation. More information on GitHub.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bartelds/gos-gpu6-cp1_adp0_144m-silver_48-orig_5e-4_cp-11000")