Automatic Speech Recognition
PEFT
Safetensors
Transformers
ELM
afri2universal
africa-g2p
african-languages
asr
audio
community-model
cross-lingual
lora
multilingual
speech
universal-orthography
whisper
whisper-large-v3-turbo
Instructions to use AfriSpeech/africa-whisper-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use AfriSpeech/africa-whisper-checkpoints with PEFT:
from peft import PeftModel from transformers import AutoModelForSpeechSeq2Seq base_model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-large-v3-turbo") model = PeftModel.from_pretrained(base_model, "AfriSpeech/africa-whisper-checkpoints") - Transformers
How to use AfriSpeech/africa-whisper-checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="AfriSpeech/africa-whisper-checkpoints")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AfriSpeech/africa-whisper-checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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