Instructions to use joaoalvarenga/model-sid-voxforge-cv-cetuc-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joaoalvarenga/model-sid-voxforge-cv-cetuc-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="joaoalvarenga/model-sid-voxforge-cv-cetuc-1")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("joaoalvarenga/model-sid-voxforge-cv-cetuc-1") model = AutoModelForCTC.from_pretrained("joaoalvarenga/model-sid-voxforge-cv-cetuc-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 507e4bf3889e62bc269203e63e7c83169afe57cf86f2084f79d96152998fd11e
- Size of remote file:
- 1.26 GB
- SHA256:
- bf22318669f1338f6c0ab0cc58b38313cf3e0bf704c41287ade27e94f3aba2a6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.