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Ghana Tts 36k GGUF

GGUF conversions of ghananlpcommunity/ghana-tts-36k for use with bluryar/VoxCPM.cpp.

KindOtherBase modelghananlpcommunity/ghana-tts-36kVersionRevision 8a1b9b2Unratedgrade

Model source

Kind
Other
File size
477 MB–2.71 GB
Base model
ghananlpcommunity/ghana-tts-36k
Version
vRevision 8a1b9b2
Updated
Nov 3, 2026
Downloads
83
Source
Hugging Face

Source description

ghana-tts-36k — GGUF quantized variants

GGUF conversions of ghananlpcommunity/ghana-tts-36k for use with bluryar/VoxCPM.cpp.

The .gguf files are backend-agnostic — the same file runs on both a CPU-only and a CUDA build of the inference engine. Only the binary you compile differs between CPU and GPU deployment, not the weight file.

Files

FileQuantAudioVAESizeNotes
ghana-tts-36k-f32.ggufF32originallargestReference/max-accuracy baseline
ghana-tts-36k-f16.ggufF16mixed
ghana-tts-36k-f16-audiovae-f16.ggufF16f16
ghana-tts-36k-q8_0.ggufQ8_0mixedRecommended for CPU
ghana-tts-36k-q8_0-audiovae-f16.ggufQ8_0f16Recommended for GPU (CUDA)
ghana-tts-36k-q4_k.ggufQ4_KmixedSmallest, more accuracy loss
ghana-tts-36k-q4_k-audiovae-f16.ggufQ4_Kf16smallest of the practical optionsFastest CPU model-only RTF; good compact CUDA option too

Which one to use

Based on bluryar/VoxCPM.cpp's own published benchmarks on the same "voxcpm" architecture family (not run on this exact checkpoint — validate on your own audio before committing to one in production):

CPU inference:

  • Default pick: ghana-tts-36k-q8_0.gguf — best full-pipeline RTF at this model scale on CPU.
  • Smaller/faster, slight accuracy trade-off: ghana-tts-36k-q4_k-audiovae-f16.gguf.

GPU (CUDA) inference:

  • Default pick: ghana-tts-36k-q8_0-audiovae-f16.gguf — best full-pipeline RTF at this model scale on CUDA.
  • Smallest CUDA-friendly option: ghana-tts-36k-q4_k-audiovae-f16.gguf.

Inference

This repo includes two scripts that build and run VoxCPM.cpp against these weights:

  • infer_cpu.sh — builds a CPU-only voxcpm_tts and runs it against ghana-tts-36k-q8_0.gguf.
  • infer_gpu.sh — builds a CUDA-enabled voxcpm_tts (requires an NVIDIA GPU + CUDA toolkit) and runs it against ghana-tts-36k-q8_0-audiovae-f16.gguf.

Usage (either script):

bash infer_cpu.sh "Text to synthesize" prompt.wav "Exact transcript of prompt.wav" out.wav
bash infer_gpu.sh "Text to synthesize" prompt.wav "Exact transcript of prompt.wav" out.wav

Swap in a different .gguf from this repo by editing the MODEL_PATH variable at the top of either script.

Sources

1 source
Hugging FacePrimaryVersion 8a1b9b2eb1b5530f27f17384868f8c6e07ed9c06
huggingface.co/walusungungulube/ghana-tts-36k-gguf/tree/8a1b9b2eb1b5530f27f17384868f8c6e07ed9c06

Verified Nov 3

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Model artifacts

7 artifacts

ghana-tts-36k-f16-audiovae-f16.gguf

gguf · 1.36 GB · SHA-256 4718cb4d6e96…a16d · Hugging Face

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ghana-tts-36k-f16.gguf

gguf · 1.36 GB · SHA-256 4718cb4d6e96…a16d · Hugging Face

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ghana-tts-36k-f32.gguf

gguf · 2.71 GB · SHA-256 77baf8801bdb…18ee · Hugging Face

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ghana-tts-36k-q4_k-audiovae-f16.gguf

gguf · Q4_K (unverified) · 545 MB · SHA-256 9d7227bee9a1…f6b7 · Hugging Face

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ghana-tts-36k-q4_k.gguf

gguf · Q4_K (unverified) · 477 MB · SHA-256 2cc677f558f2…bcd0 · Hugging Face

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ghana-tts-36k-q8_0-audiovae-f16.gguf

gguf · Q8_0 (unverified) · 811 MB · SHA-256 552b37352bf2…02cf · Hugging Face

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ghana-tts-36k-q8_0.gguf

gguf · Q8_0 (unverified) · 766 MB · SHA-256 3668d62ab177…5617 · Hugging Face

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Source excerpts

3 excerpts

--- license: mit tags: - text-to-speech - voxcpm - gguf - ghana-tts base_model: ghananlpcommunity/ghana-tts-36k --- # ghana-tts-36k — GGUF quantized variants GGUF conversions of [`ghananlpcommunity/ghana-tts-36k`](https://huggingface.co/ghananlpcommunity/ghana-tts-36k) for use with [bluryar/VoxCPM.cpp](https://github.com/bluryar/VoxCPM.cpp). **The `.gguf` files are backend-agnostic** — the same file runs on both a CPU-only and a CUDA build of the inference engine. Only the *binary* you compile differs between CPU and GPU deployment, not the weight file. ## Files | File | Quant | AudioVAE | Size | Notes | |---|---|---|---|---| | `ghana-tts-36k-f32.gguf` | F32 | original | largest | Reference/max-accuracy baseline | | `ghana-tts-36k-f16.gguf` | F16 | mixed | | | | `ghana-tts-36k-f16-audiovae-f16.gguf` | F16 | f16 | | | | `ghana-tts-36k-q8_0.gguf` | Q8_0 | mixed | | **Recommended for CPU** | | `ghana-tts-36k-q8_0-audiovae-f16.gguf` | Q8_0 | f16 | | **Recommended for GPU (CUDA)** | | `ghana-tts-36k-q4_k.gguf` | Q4_K | mixed | | Smallest, more accuracy loss | | `ghana-tts-36k-q4_k-audiovae-f16.gguf` | Q4_K | f16 | smallest of the practical options | Fastest CPU model-only RTF; good compact CUDA option too | ## Which one to use Based on [bluryar/VoxCPM.cpp](https://github.com/bluryar/VoxCPM.cpp)'s own published benchmarks on the same `"voxcpm"` architecture family (not run on this exact checkpoint — validate on your own audio before committing to one in production): **CPU inference:** - Default pick: **`ghana-tts-36k-q8_0.gguf`** — best full-pipeline RTF at this model scale on CPU. - Smaller/faster, slight accuracy trade-off: `ghana-tts-36k-q4_k-audiovae-f16.gguf`. **GPU (CUDA) inference:** - Default pick: **`ghana-tts-36k-q8_0-audiovae-f16.gguf`** — best full-pipeline RTF at this model scale on CUDA. - Smallest CUDA-friendly option: `ghana-tts-36k-q4_k-audiovae-f16.gguf`. ## Inference This repo includes two scripts that build and run [VoxCPM.cpp](https://github.com/bluryar/VoxCPM.cpp) against these weights: - `infer_cpu.sh` — builds a CPU-only `voxcpm_tts` and runs it against `ghana-tts-36k-q8_0.gguf`. - `infer_gpu.sh` — builds a CUDA-enabled `voxcpm_tts` (requires an NVIDIA GPU + CUDA toolkit) and runs it against `ghana-tts-36k-q8_0-audiovae-f16.gguf`. Usage (either script): ```bash bash infer_cpu.sh "Text to synthesize" prompt.wav "Exact tr...

Source context: 83 downloads · 0 likes · Pipeline text-to-speech · Library voxcpm · Repo walusungungulube/ghana-tts-36k-gguf

Source context: 109 downloads · 0 likes · Pipeline text-to-speech · Library voxcpm · Repo walusungungulube/ghana-tts-36k-gguf