Instructions to use Soupis/BaseB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Soupis/BaseB with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Soupis/BaseB")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Soupis/BaseB") model = AutoModelForSpeechSeq2Seq.from_pretrained("Soupis/BaseB", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0603c65a5e919377f7bfc66c60a477e2089cf09848f58018e67d482901cb409c
- Size of remote file:
- 5.24 kB
- SHA256:
- 1602117d04c48d1f63721d5f3be0d471eb2a31099d60a8e82ba273c5675ede6b
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