Instructions to use Soupis/BaseC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Soupis/BaseC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Soupis/BaseC")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Soupis/BaseC") model = AutoModelForSpeechSeq2Seq.from_pretrained("Soupis/BaseC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7137a63586191af43f10f41be52fee785c6713a90582cde9e32f532e82970754
- Size of remote file:
- 5.24 kB
- SHA256:
- c7846cc444046e4f631591af18ccb4fffb846b87690bc25e5843885ad3b9dc79
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