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AfroLogicInsect/whisper-finetuned-original

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face

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AfroLogicInsect/whisper-finetuned-original

Fine-tuned Whisper model for speech recognition

Model Details

—Model Type: Whisper (Fine-tuned)
—Language: English
—Data Type: mixed precision
—Use Cases: Speech-to-text transcription

Usage

python

from transformers import WhisperProcessor, WhisperForConditionalGeneration
import librosa

# Load model and processor
processor = WhisperProcessor.from_pretrained("AfroLogicInsect/whisper-finetuned-original")
model = WhisperForConditionalGeneration.from_pretrained("AfroLogicInsect/whisper-finetuned-original")

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

# Process
input_features = processor(audio, sampling_rate=16000, return_tensors="pt").input_features

# Generate transcription
with torch.no_grad():
    predicted_ids = model.generate(input_features)
    transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)[0]

print(transcription)

Training Details

—Base Model: OpenAI Whisper
—Training Dataset: [Add your dataset details]
—Training Parameters: [Add your training parameters]
—Evaluation Metrics: [Add your evaluation results]

Limitations and Biases

—This model may have biases present in the training data
—Performance may vary on different accents or audio qualities
—Recommended for English speech recognition tasks

Citation

If you use this model, please cite:

bibtex

@misc{whisper-finetuned,
  author = {Daniel AMAH},
  title = {Fine-tuned Whisper Model},
  year = {2024},
  publisher = {Hugging Face},
  url = {https://huggingface.co/AfroLogicInsect/whisper-finetuned-original}
}