Roo-Voice · MOSS-TTS-Local-Transformer · BF16 (PyTorch / CUDA)
Roo's voice — that signature baritone with the estuary accent that stands the hair up on the back of your neck — as a standard PyTorch checkpoint that runs on any NVIDIA GPU. Load it, and Roo can whisper to you all day long.
A BF16 (bfloat16) checkpoint of a full-model supervised fine-tune of
MOSS-TTS-Local-Transformer,
trained on Roo's own recordings and specialised on his single voice. This is the PC / NVIDIA-GPU
form — for Apple Silicon use the MLX 8-bit build.
⚠️ What actually makes the voice — read first
This is a reference-conditioned model, and both halves matter:
- The fine-tune is what makes it Roo. The base model has never heard this speaker — a base model plus any reference clip will not give you Roo's baritone or his estuary accent. That voice lives in the weights, put there by the supervised fine-tune on his recordings.
- The reference completes the delivery.
reference.wav(bundled) conditions the fine-tuned model at inference and is required to produce the voice.
So the product is this fine-tune + reference.wav, together — not a text-only model, and not a
generic voice-cloner (swap the reference and it isn't Roo, because the accent and timbre are the
fine-tune's, not the clip's).
What it is
| Voice | Single speaker — Roo (baritone, estuary accent), 24 kHz mono |
| Format | PyTorch safetensors, bfloat16, ≈ 5.8 GB |
| Architecture | MossTTSLocal (trust_remote_code), 556 tensors, full-model SFT (not LoRA/adapter) |
| Runs on | Any CUDA NVIDIA GPU with PyTorch (the standard MOSS-TTS Local inference path) |
| Base | OpenMOSS-Team/MOSS-TTS-Local-Transformer @ 12aa734e4f11a7b3fdf4eb0ad2aa2029675ffc2e |
| Audio codec | OpenMOSS-Team/MOSS-Audio-Tokenizer @ 3cd226ba2947efa357ef453bcad111b6eafba782 |
Usage
This is a drop-in fine-tuned MossTTSLocal checkpoint — run it exactly like the base
MOSS-TTS-Local-Transformer, just point the loader at this repo and pass reference.wav as the
reference. The supported inference paths are:
- OpenMOSS MOSS-TTS reference pipeline — https://github.com/OpenMOSS/MOSS-TTS (PyTorch, CUDA).
- vLLM-Omni and SGLang-Omni, which support the
MossTTSLocalarchitecture with an OpenAI-compatible/v1/audio/speechendpoint and voice cloning.
Decoding contract for this voice: seed 42, temperature 1.0, top-k 50, top-p 0.95, repetition
penalty 1.1, 32 RVQ codebooks. Supply reference.wav as the cloning/reference audio.
Smaller builds
An INT8 (bitsandbytes) build for tighter VRAM is planned as a sibling repo. On Apple Silicon, the MLX 8-bit build is ~3.6 GB.
Limitations
- Reference-conditioned — the bundled
reference.wavmust ride along; there is no text-only path. - Single voice by design (this is Roo, not a multi-speaker system).
- BF16 is a near-lossless downcast of the accepted FP32 fine-tune.
Provenance & license
Quantized/exported form of an accepted single-speaker MOSS-TTS Local supervised fine-tune. The base model and audio codec are Apache-2.0 (OpenMOSS); weights derived from them are redistributed here under the same license.