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:
- a146f5fea01ca2a0f559562e030141846f35e7ba9a71079746d27ced38f37c51
- Size of remote file:
- 151 MB
- SHA256:
- ac8ddaaabc1f299258dd7b8127390cdfe1654b95ce9982e9146142f263950856
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.