Instructions to use spow12/Visual-novel-transcriptor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use spow12/Visual-novel-transcriptor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="spow12/Visual-novel-transcriptor")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("spow12/Visual-novel-transcriptor") model = AutoModelForSpeechSeq2Seq.from_pretrained("spow12/Visual-novel-transcriptor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 070680d354d137fe72e46eea19767ef80bac54441f93250d113231c369fd8427
- Size of remote file:
- 3.02 GB
- SHA256:
- d18376b8c10a09b5cb48145870db0947664f9af3fc57bf9867e2c613360fc786
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