Instructions to use rAzOr1/model_from_hugginface_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rAzOr1/model_from_hugginface_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="rAzOr1/model_from_hugginface_model")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("rAzOr1/model_from_hugginface_model") model = AutoModelForAudioClassification.from_pretrained("rAzOr1/model_from_hugginface_model") - Notebooks
- Google Colab
- Kaggle
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="rAzOr1/model_from_hugginface_model")# Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("rAzOr1/model_from_hugginface_model")
model = AutoModelForAudioClassification.from_pretrained("rAzOr1/model_from_hugginface_model")Quick Links
# Gated model: Login with a HF token with gated access permission hf auth login