Instructions to use hts98/Model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hts98/Model2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hts98/Model2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hts98/Model2") model = AutoModelForSpeechSeq2Seq.from_pretrained("hts98/Model2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df6b8112ff193dd13532f039f2c4f0ae7048dee84e09087a5dc1f2ad178600e3
- Size of remote file:
- 4.03 kB
- SHA256:
- 2f4293876c25b299bd3cfee9ab3f1eabe109a9248024d2e700d225862b43903c
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