Automatic Speech Recognition
Transformers
Safetensors
Fanti
wav2vec2-bert
speech
asr
african-languages
w2v-bert
khaya
Eval Results (legacy)
Instructions to use KhayaAI/w2v-bert-fat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KhayaAI/w2v-bert-fat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="KhayaAI/w2v-bert-fat")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("KhayaAI/w2v-bert-fat") model = AutoModelForCTC.from_pretrained("KhayaAI/w2v-bert-fat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add arXiv:2607.21540 tag + paper link; update model card
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initial commit
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