Instructions to use Alwaly/whisper-medium-wolof with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alwaly/whisper-medium-wolof with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Alwaly/whisper-medium-wolof")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Alwaly/whisper-medium-wolof") model = AutoModelForSpeechSeq2Seq.from_pretrained("Alwaly/whisper-medium-wolof", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Create Handler.py
#2
by YUXCulturalAILab - opened
Fix forced_decoder_ids deprecation for Wolof model
- Removes deprecated forced_decoder_ids parameter causing 400 errors
- Sets proper Wolof language configuration (language="wo")
- Handles multiple audio input formats (binary, base64, paths)
- Ensures compatibility with modern transformers library