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")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration") model = AutoModelForMultimodalLM.from_pretrained("onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download onnx/decoder_model_merged.onnx from onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 22.9 kB
-
https://huggingface.co/onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration/resolve/main/onnx/decoder_model_merged.onnx
- Command line
-
hf download hf://onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration/onnx/decoder_model_merged.onnx
-
curl -L -o decoder_model_merged.onnx https://huggingface.co/onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration/resolve/main/onnx/decoder_model_merged.onnx
22.9 kB
- Xet hash:
- aa5bfcaac01665751ac0d4b6d2847856819cd72527319c2c2ba7bed05abeec64
- Size of remote file:
- 22.9 kB
- SHA256:
- 50266c4481e65673eb53ed2fdbe5ab291a63553022b9b277c642220e4fd4dd60
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