Audio-Text-to-Text
Transformers
Safetensors
vibevoice_asr
automatic-speech-recognition
ASR
Diarization
Speech-to-Text
Transcription
Eval Results
Instructions to use microsoft/VibeVoice-ASR-HF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/VibeVoice-ASR-HF with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("microsoft/VibeVoice-ASR-HF") model = AutoModelForMultimodalLM.from_pretrained("microsoft/VibeVoice-ASR-HF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model-00003-of-00008.safetensors from microsoft/VibeVoice-ASR-HF: direct link, hf CLI and curl.
- Browser
- Download file 2.47 GB
-
https://huggingface.co/microsoft/VibeVoice-ASR-HF/resolve/main/model-00003-of-00008.safetensors
- Command line
-
hf download hf://microsoft/VibeVoice-ASR-HF/model-00003-of-00008.safetensors
-
curl -L -o model-00003-of-00008.safetensors https://huggingface.co/microsoft/VibeVoice-ASR-HF/resolve/main/model-00003-of-00008.safetensors
2.47 GB
- Xet hash:
- 73f659e4e71e6819c5efc23f58d14664710549956c14e609d6ddb5a4438f2e73
- Size of remote file:
- 2.47 GB
- SHA256:
- 30f574c764550d26c654cc3f5dd000b90b0c3305db955267c577001c1013fdf7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.