Roo-Voice_MOSS_TTS_LT_bf16

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

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 MossTTSLocal architecture with an OpenAI-compatible /v1/audio/speech endpoint 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.wav must 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.