Instructions to use Soupis/small-trsc-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Soupis/small-trsc-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Soupis/small-trsc-3")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Soupis/small-trsc-3") model = AutoModelForSpeechSeq2Seq.from_pretrained("Soupis/small-trsc-3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43767f2efb1b0bbf46275b03eff5563fc7cd7e49de337d107bac0948d65f12e0
- Size of remote file:
- 1.93 GB
- SHA256:
- 5876ae7cb782111da974992620922ea86bb52c6d7424bdae08a54539e7519635
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