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, 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/audio_encoder.onnx_data from onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 1.47 MB
-
https://huggingface.co/onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration/resolve/main/onnx/audio_encoder.onnx_data
- Command line
-
hf download hf://onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration/onnx/audio_encoder.onnx_data
-
curl -L -o audio_encoder.onnx_data https://huggingface.co/onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration/resolve/main/onnx/audio_encoder.onnx_data
1.47 MB
- Xet hash:
- 6dbb85d334cf5b2617c5d6d619e2f328137c24d0a56545d8fa259a6fb78c3a52
- Size of remote file:
- 1.47 MB
- SHA256:
- d8ddfcda815049c9c3212fc41d6d3d93a3b8f8251b66a82d0f0e5b1b0cc79173
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