Automatic Speech Recognition
Transformers
Safetensors
VibeVoice
ASR
Transcription
Speech-to-Text
Streaming
Instructions to use microsoft/VibeVoice-ASR-Streaming-1.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/VibeVoice-ASR-Streaming-1.5B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="microsoft/VibeVoice-ASR-Streaming-1.5B")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, VibeVoiceForASRStreamingTraining processor = AutoProcessor.from_pretrained("microsoft/VibeVoice-ASR-Streaming-1.5B") model = VibeVoiceForASRStreamingTraining.from_pretrained("microsoft/VibeVoice-ASR-Streaming-1.5B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from microsoft/VibeVoice-ASR-Streaming-1.5B: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/microsoft/VibeVoice-ASR-Streaming-1.5B/resolve/main/tokenizer.json
- Command line
-
hf download hf://microsoft/VibeVoice-ASR-Streaming-1.5B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/microsoft/VibeVoice-ASR-Streaming-1.5B/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 73dfaf86d7cc374881c393c0b96ff3dff40808c151d94af432b9b9d5840ffa79
- Size of remote file:
- 11.4 MB
- SHA256:
- d198a051741ee47805797b744e6524c259b08a59b58d1ec159cfd7f1da5f2df7
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