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:
- 1666d02b1ed54ab764b4d592eb59c99722eea813bf3c2f5c3a98ad1fa7815633
- Size of remote file:
- 407 MB
- SHA256:
- c8201154250fca6f80d2813953c7404d266217b0bec39490a16c5cb9841ed1f6
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