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:
- 0ac0998da57ca5af7f574c4e23b001cab07645e5e70cb4409ee516534cf1ff79
- Size of remote file:
- 653 MB
- SHA256:
- 83eb8b2b4957ff6a467ca37538a54935dbc4f44983dd2e8c61a72922d38d1a59
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