Instructions to use IABDs8a/lara-medium-R-Equipo2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IABDs8a/lara-medium-R-Equipo2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="IABDs8a/lara-medium-R-Equipo2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("IABDs8a/lara-medium-R-Equipo2") model = AutoModelForSpeechSeq2Seq.from_pretrained("IABDs8a/lara-medium-R-Equipo2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f6a3ae695e5a72c4abd77df73470930fa50bcf7f617318f5024269f2f9328c0c
- Size of remote file:
- 3.06 GB
- SHA256:
- eaebbd15b7ae3c4249b8059b0600ad682dda04bd0bc049246659192b3a13ba49
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