Instructions to use KevinKibe/omniASR-CTC-300M-v2-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KevinKibe/omniASR-CTC-300M-v2-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="KevinKibe/omniASR-CTC-300M-v2-GGUF")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("KevinKibe/omniASR-CTC-300M-v2-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6fefa475d32c996474859c8f5acc4a0eff0d23cd84ce80882ae129d9648af119
- Size of remote file:
- 292 MB
- SHA256:
- 4c5b65b480e266a7f48145d41fb2e7f8100f1e380f3399cb5ab5660baf29a061
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.