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:
- 9137fc48cc9951b0d51fd5f172b4b562476d09113f0fb26f82b4b636932cb9ea
- Size of remote file:
- 309 MB
- SHA256:
- 1c46aa1fd3b8d42158e80cb00006b266444c1ad5ea35a21735dbc83cdfd5bf09
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