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+voice-en-Emma.gguf filter=lfs diff=lfs merge=lfs -text
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+vibevoice-realtime-0.5B-q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+license: mit
+library_name: vibevoice.cpp
+tags:
+  - tts
+  - asr
+  - speech
+  - vibevoice
+  - gguf
+  - ggml
+base_model:
+  - microsoft/VibeVoice-Realtime-0.5B
+  - microsoft/VibeVoice-ASR
+---
+
+# vibevoice.cpp — quantized model bundle
+
+Quantized GGUF weights for [vibevoice.cpp](https://github.com/mudler/vibevoice.cpp),
+a C/C++ port of Microsoft VibeVoice (TTS + ASR) on top of `ggml`.
+
+| File | Source | Quant | Size |
+| ---- | ------ | ----- | ---- |
+| `vibevoice-realtime-0.5B-q8_0.gguf` | `microsoft/VibeVoice-Realtime-0.5B` | Q8_0 (matmul) + F16 | ~1.6 GB |
+| `vibevoice-asr-q8_0.gguf`           | `microsoft/VibeVoice-ASR`           | Q8_0 (matmul) + F16 | ~13 GB |
+| `voice-en-Carter_man.gguf`          | upstream voice prompt cache         | F16                  | 8 MB |
+| `voice-en-Emma.gguf`                | upstream voice prompt cache         | F16                  | 6 MB |
+| `tokenizer.gguf`                    | Qwen2.5 BPE + VibeVoice specials    | —                    | 6 MB |
+
+## Quantization scheme
+
+`scripts/quantize_gguf.py` in the source repo selectively quantizes only the
+LM matmul weights — attention q/k/v/o, ffn gate/up/down, and lm_head — to
+Q8_0. Everything else (1-D conv kernels, RMSNorm scales, biases,
+layer-scale gammas, token embeddings, small scalars) passes through
+unchanged. The conv1d implementation in vibevoice.cpp casts kernels to F16
+inline rather than dequantizing on the fly, so quantizing those would
+corrupt the convolution outputs.
+
+Q8_0 was chosen because it's pure-Python implementable in `gguf-py` and
+gives a ~60% size reduction on the 7B ASR model with no measurable
+quality regression in the closed-loop TTS → ASR roundtrip test.
+
+## Quickstart
+
+```bash
+git clone --recursive https://github.com/mudler/vibevoice.cpp
+cd vibevoice.cpp && cmake -B build -DVIBEVOICE_BUILD_TESTS=ON && cmake --build build -j
+
+# Pull this bundle
+mkdir -p models && cd models
+hf download mudler/vibevoice.cpp-models --local-dir .
+cd ..
+
+# TTS
+build/bin/vibevoice-cli tts \
+    --model models/vibevoice-realtime-0.5B-q8_0.gguf \
+    --voice models/voice-en-Carter_man.gguf \
+    --tokenizer models/tokenizer.gguf \
+    --text "Hello world this is a test of the synthesis system." \
+    --out hello.wav
+
+# ASR
+build/bin/vibevoice-cli asr \
+    --model models/vibevoice-asr-q8_0.gguf \
+    --tokenizer models/tokenizer.gguf \
+    --audio hello.wav
+# -> [{"Start":0,"End":2.8,"Speaker":0,"Content":"Hello world, this is a test of the synthesis system."}]
+```
+
+## Closed-loop verification
+
+The `test_closed_loop` ctest in vibevoice.cpp runs TTS → ASR end-to-end
+and asserts ≥80% source-word recall in the recovered transcript. With
+this bundle (both Q8_0 models) it passes at 10/10 (100 %).
+
+## License
+
+Weights are derived from Microsoft VibeVoice
+([VibeVoice-Realtime-0.5B](https://huggingface.co/microsoft/VibeVoice-Realtime-0.5B)
+and [VibeVoice-ASR](https://huggingface.co/microsoft/VibeVoice-ASR));
+follow the upstream model licenses for use. The conversion + quantization
+tooling is released under MIT as part of vibevoice.cpp.

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