Instructions to use iisking/test_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iisking/test_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="iisking/test_2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("iisking/test_2") model = AutoModelForSpeechSeq2Seq.from_pretrained("iisking/test_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd75cb3d1a059915aa0822ba22b2c9578ac4f7754079f044489aef9e488e7cdf
- Size of remote file:
- 3.27 GB
- SHA256:
- da66496c753afac736f992c168f06cb59a185fe7fd27dc885d768c8acbe3b211
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