Automatic Speech Recognition
Transformers
Safetensors
seamless_m4t_v2
audio
speech
african-languages
multilingual
simba
low-resource
speech-recognition
asr
Instructions to use UBC-NLP/Simba-S with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UBC-NLP/Simba-S with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="UBC-NLP/Simba-S")# Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("UBC-NLP/Simba-S") model = AutoModelForSpeechSeq2Seq.from_pretrained("UBC-NLP/Simba-S") - Notebooks
- Google Colab
- Kaggle