Automatic Speech Recognition
Transformers
Safetensors
Hausa
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use EYEDOL/whisper-tiny-hausa4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EYEDOL/whisper-tiny-hausa4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="EYEDOL/whisper-tiny-hausa4")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("EYEDOL/whisper-tiny-hausa4") model = AutoModelForSpeechSeq2Seq.from_pretrained("EYEDOL/whisper-tiny-hausa4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66c008b66e07750feb3014c8de4278ec3b1b6743e18c2ffef4335ff49ca75a93
- Size of remote file:
- 5.39 kB
- SHA256:
- 9e0df7623e01608575510f7a6b329ebdf38c8ac95ae36201ea75010818d4e5c2
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