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/embed_tokens.onnx_data from onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 33.6 MB
-
https://huggingface.co/onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration/resolve/main/onnx/embed_tokens.onnx_data
- Command line
-
hf download hf://onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration/onnx/embed_tokens.onnx_data
-
curl -L -o embed_tokens.onnx_data https://huggingface.co/onnx-internal-testing/tiny-random-VoxtralRealtimeForConditionalGeneration/resolve/main/onnx/embed_tokens.onnx_data
33.6 MB
- Xet hash:
- 4eda588c323d4d46666341268969176af4562b9369a6fa0f123a0a3a1289dade
- Size of remote file:
- 33.6 MB
- SHA256:
- 3d690b2b1766e3c97f60c388849de457859720c40d4a11bcf68e2b2663de8712
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