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:
- d86b1e43d15117a9d28f73415de779bdb707aaff962fd4824fc92ffc31a133ea
- Size of remote file:
- 4.09 kB
- SHA256:
- 50cf1a290f9c80fdbfde6fd771d7eb1b1f5cba9fab529802fd40ddf2595bacbb
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