You can deploy this model and start earning money today!

ahmad1703/
whisper_ee

Name: whisper_ee
Availability: InStock

pytorch

whisper_classifier

Views

No views yet

Whisper Binary Audio Classifier

This model performs binary classification on audio using OpenAI's Whisper-small as a base model. It's designed to be used via the Hugging Face API for inference.

Model Details

Base model: openai/whisper-small
Task: Binary Audio Classification
Output: Binary classification (0 or 1)

API Usage

python

from transformers import WhisperProcessor, pipeline
import librosa

# Load processor and pipeline
processor = WhisperProcessor.from_pretrained("ahmad1703/whis_ee")
classifier = pipeline("audio-classification", model="ahmad1703/whis_ee")

# Prepare your audio
audio_path = "path/to/your/audio.wav"
audio, sr = librosa.load(audio_path, sr=16000)

# Get prediction
prediction = classifier(audio)
print(f"Prediction: {prediction}")

Limitations

This model works best with clean audio recordings
Input audio should have a sampling rate of 16kHz
[Add any other limitations here]

Contact

[Your contact information]

ahmad1703/whisper_ee