Instructions to use hts98/Model3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hts98/Model3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hts98/Model3")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hts98/Model3") model = AutoModelForSpeechSeq2Seq.from_pretrained("hts98/Model3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61d08c1c9ce9f71cb71afb929869916bc79406376739e5329f1fc2e0100834b0
- Size of remote file:
- 3.06 GB
- SHA256:
- 681d28f4b31ded727606389010e76fd46f2c2d1915fbafc74ff0f7b7d3818dd1
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