Automatic Speech Recognition
Safetensors
VibeVoice
vibevoice.c
speculative-decoding
dflash
awq
compressed-tensors
speech-recognition
4-bit precision
Instructions to use Ar4ikov/VibeVoice-ASR-Streaming-7B-AWQ-W4A16-ASYM-DFlash2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- VibeVoice
How to use Ar4ikov/VibeVoice-ASR-Streaming-7B-AWQ-W4A16-ASYM-DFlash2 with VibeVoice:
import torch, soundfile as sf, librosa, numpy as np from vibevoice.processor.vibevoice_processor import VibeVoiceProcessor from vibevoice.modular.modeling_vibevoice_inference import VibeVoiceForConditionalGenerationInference # Load voice sample (should be 24kHz mono) voice, sr = sf.read("path/to/voice_sample.wav") if voice.ndim > 1: voice = voice.mean(axis=1) if sr != 24000: voice = librosa.resample(voice, sr, 24000) processor = VibeVoiceProcessor.from_pretrained("Ar4ikov/VibeVoice-ASR-Streaming-7B-AWQ-W4A16-ASYM-DFlash2") model = VibeVoiceForConditionalGenerationInference.from_pretrained( "Ar4ikov/VibeVoice-ASR-Streaming-7B-AWQ-W4A16-ASYM-DFlash2", torch_dtype=torch.bfloat16 ).to("cuda").eval() model.set_ddpm_inference_steps(5) inputs = processor(text=["Speaker 0: Hello!\nSpeaker 1: Hi there!"], voice_samples=[[voice]], return_tensors="pt") audio = model.generate(**inputs, cfg_scale=1.3, tokenizer=processor.tokenizer).speech_outputs[0] sf.write("output.wav", audio.cpu().numpy().squeeze(), 24000) - Notebooks
- Google Colab
- Kaggle
File size: 1,001 Bytes
463a3ca | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | {
"source_revision": "60d858b518b4e19d404af3737f848fc185b30177",
"source_safetensors_bytes": 17348198658,
"output_safetensors_bytes": 7000335408,
"compression_ratio": 2.478195350207711,
"quantized_projections": 196,
"method": "Activation-aware AWQ using llm-compressor; exact layout repack into AWQ GEMM",
"lm_head": "BF16",
"scheme": "W4A16_ASYM",
"group_size": 128,
"duo_scaling": "both",
"grid_points": 40,
"calibration_samples": 256,
"audio_calibration_samples": 128,
"text_calibration_samples": 128,
"calibration_stats": {
"audio_sessions": 128,
"audio_rows_mean": 944.7734375,
"audio_rows_total": 120931,
"truncated_at_2048": 0
},
"max_sequence_length": 2048,
"packing_validation": "All integer weight and zero-point codes round-trip exactly; all scale values preserved exactly",
"pruning": {
"removed_prefixes": [
"model.acoustic_tokenizer.decoder."
],
"removed_bf16_bytes": 687391938,
"speech_bytes": 1429418752
}
} |