Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Adhola
English
whisper
japadhola
adhola
asr
speech
uganda
buair
buaiir
Instructions to use BUAIR/whisper-small-jap with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BUAIR/whisper-small-jap with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="BUAIR/whisper-small-jap")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("BUAIR/whisper-small-jap") model = AutoModelForSpeechSeq2Seq.from_pretrained("BUAIR/whisper-small-jap", device_map="auto") - Notebooks
- Google Colab
- Kaggle
BUAIR Whisper-Small Japadhola (BUAIR/whisper-small-jap)
Fine-tuned openai/whisper-small for Japadhola (Adhola, ISO 639-3: adh)
automatic speech recognition. Maintained by BUAIIR โ Busitema University AI & Innovation Research Lab.
This is the BUAIR org release. Source copy: Bateesa/whisper-small-jap.
Related speech datasets
- BUAIR/popolivoice โ Papoli community speech
- BUAIR/buaiir_voice_jap โ student read speech
Load
from transformers import pipeline
asr = pipeline(
"automatic-speech-recognition",
model="BUAIR/whisper-small-jap",
)
print(asr("path/to/audio.wav"))
Updated: 2026-08-13
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Model tree for BUAIR/whisper-small-jap
Base model
openai/whisper-small