Instructions to use trl-internal-testing/tiny-VoxtralForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trl-internal-testing/tiny-VoxtralForConditionalGeneration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="trl-internal-testing/tiny-VoxtralForConditionalGeneration")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("trl-internal-testing/tiny-VoxtralForConditionalGeneration") model = AutoModelForSpeechSeq2Seq.from_pretrained("trl-internal-testing/tiny-VoxtralForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73003d1cf7ace66f694fd7519cbf2f43ae9c3675a78510441f3371d1f57f9133
- Size of remote file:
- 14.9 MB
- SHA256:
- 4aaf3836c2a5332f029ce85a7a62255c966f47b6797ef81dedd0ade9c862e4a8
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