Audio-Text-to-Text
Transformers
Safetensors
vibevoice_asr
automatic-speech-recognition
ASR
Diarization
Speech-to-Text
Transcription
torchao
Instructions to use Matir/VibeVoice-ASR-HF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Matir/VibeVoice-ASR-HF with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Matir/VibeVoice-ASR-HF") model = AutoModelForMultimodalLM.from_pretrained("Matir/VibeVoice-ASR-HF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 3,398 Bytes
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"num_filters": 32,
"rms_norm_eps": 1e-05,
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"architectures": [
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"dtype": "bfloat16",
"model_type": "vibevoice_asr",
"quantization_config": {
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"quant_method": "torchao",
"quant_type": {
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"max_position_embeddings": 131072,
"max_window_layers": 28,
"model_type": "qwen2",
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"num_hidden_layers": 28,
"num_key_value_heads": 4,
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"rope_parameters": {
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