Automatic Speech Recognition
Transformers
Safetensors
Hausa
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use EYEDOL/whisper-tiny-hausa2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EYEDOL/whisper-tiny-hausa2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="EYEDOL/whisper-tiny-hausa2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("EYEDOL/whisper-tiny-hausa2") model = AutoModelForSpeechSeq2Seq.from_pretrained("EYEDOL/whisper-tiny-hausa2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c452806e3695a817d275600225d8069a85e995ce9a09d3455bde0b611666e34
- Size of remote file:
- 5.39 kB
- SHA256:
- c2fe870dfe3ee7c4d163b02327bdcbcb8440d51d0765274c769c295fe7c8dc34
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