Instructions to use onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration") model = AutoModelForSpeechSeq2Seq.from_pretrained("onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
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