Instructions to use salixc/dielect_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use salixc/dielect_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="salixc/dielect_classification_model")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("salixc/dielect_classification_model") model = AutoModelForAudioClassification.from_pretrained("salixc/dielect_classification_model") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("salixc/dielect_classification_model")
model = AutoModelForAudioClassification.from_pretrained("salixc/dielect_classification_model")Quick Links
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="salixc/dielect_classification_model")