Instructions to use Soupis/BaseA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Soupis/BaseA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Soupis/BaseA")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Soupis/BaseA") model = AutoModelForSpeechSeq2Seq.from_pretrained("Soupis/BaseA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ebe0219810ba4636b30956920eba2b4612142652c24da4286dbd4163946496d3
- Size of remote file:
- 5.24 kB
- SHA256:
- d2e32a0809dbeaa1359f0246bfc18958abaaff45266df7621ee07aef08f9c819
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