Instructions to use chironbang/dsn_afrispeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chironbang/dsn_afrispeech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="chironbang/dsn_afrispeech")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("chironbang/dsn_afrispeech") model = AutoModelForSpeechSeq2Seq.from_pretrained("chironbang/dsn_afrispeech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca26090a4ed87640202915cbebb9bd0c64b2cd3c139e74bced879ccbaaacf030
- Size of remote file:
- 3.77 kB
- SHA256:
- d6f6214d5267c82b4ebd2675e65a15aac2f879b89c02cfae08e46c97bd1e45f8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.