build-small-hackathon/baby-mynah-welsh

baby mynah — Welsh accent (LoRA for VoxCPM-0.5B)

A LoRA adapter that voices VoxCPM-0.5B in the Welsh accent of a single VCTK speaker. One of the accent experts behind the baby mynah Space, where you can slide between any two of them in weight space.

What it is

• Base model: openbmb/VoxCPM-0.5B (OpenBMB), a tokenizer-free TTS model. This repo holds only the LoRA delta (~28 MB) — you also need the base model.
• Accent: Welsh (Cardiff), learned from a single VCTK speaker (p253, age 22, female) — ~8 minutes of read speech.
• Not PEFT. VoxCPM uses a custom LoRALinear, so this loads through the baby-mynah loader, not peft. The weights file stores, per target Linear, <prefix>.lora_A (r, in) and <prefix>.lora_B (out, r); the layer applies out += (alpha/r) * (x @ A^T @ B^T).

Training

Method	LoRA (rank 32, alpha 32, dropout 0)
Target modules	q/k/v/o_proj on both the LM and the DiT
Steps	800 (effective batch 4 = batch 1 x grad-accum 4)
LR	1e-4, 50 warmup, weight decay 0.01
Audio	~8 min, 16 kHz mono

Usage

These adapters are meant to be blended, which is what the Space does. To load one on its own, use the project's load_adapter / blend_into_model helpers (see scripts/blend.py):

from blend import load_adapter, blend_into_model, restore_weights, scaling_from_config
from voxcpm import VoxCPM

model = VoxCPM.from_pretrained(hf_model_id="openbmb/VoxCPM-0.5B", optimize=False, device="cuda")
adapter = load_adapter("path/to/this/adapter")        # {prefix: (A, B)}
scaling = scaling_from_config("path/to/this/adapter")  # alpha / r

# alpha=1.0 applies this expert fully; restore afterwards (surgery is in-place).
snap = blend_into_model(model.tts_model, adapter, adapter, alpha=1.0, scaling=scaling)
wav = model.generate(text="Hello! I am a very small bird.", normalize=True)
restore_weights(model.tts_model, snap)

License & attribution

• LoRA weights released under CC BY 4.0, following the VCTK corpus (CSTR, University of Edinburgh) they were trained on.
• Base model VoxCPM-0.5B by OpenBMB, Apache-2.0.