Instructions to use speechdata/detect-speech-background-noise with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use speechdata/detect-speech-background-noise with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="speechdata/detect-speech-background-noise")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("speechdata/detect-speech-background-noise") model = AutoModelForAudioClassification.from_pretrained("speechdata/detect-speech-background-noise") - Notebooks
- Google Colab
- Kaggle
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="speechdata/detect-speech-background-noise")# Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("speechdata/detect-speech-background-noise")
model = AutoModelForAudioClassification.from_pretrained("speechdata/detect-speech-background-noise")Quick Links
private for now, more details coming soon
very experimental model so please DM me on X for access https://x.com/realmrfakename
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Model tree for speechdata/detect-speech-background-noise
Base model
openai/whisper-tiny
# Gated model: Login with a HF token with gated access permission hf auth login