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:
- 9647e034258d5bb5b8ae831c07f307a88d4a0467340ea6d14dc8c608545b7145
- Size of remote file:
- 309 MB
- SHA256:
- 4d4a912b289e439152ada77bd258927ef1a18c1709e7ece16c34d403080ab3d8
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