LAION-Box Emotional v0.7 β rank-128 (expressive voice-acting TTS, fully-merged)
Rank-128 variant of the emotional fine-tune. Three fully-merged standalone LTX-2.3
3.3B audio-only DiT checkpoints β use directly, no LoRA loading.
(Companion repos: rank-32 = laion/LAION-Box-Emotional-v0.7, rank-64/128 = -r64 / -r128.)
Lineage
Lightricks/LTX-2.3 (3.3B audio-only DiT) β DramaBox (Resemble AI, IC-LoRA fine-tune of LTX-2.3)
β LAION run16 v0.7 LoRA (rank 256, merged) β emotion LoRA rank 128, Ξ± 128 (10 epochs, merged).
Files
| model (this repo) | LoRA step | flow loss |
|---|---|---|
LAION-Box-Emotional-v0.7-r128_best1_step100.safetensors |
100 | 0.188 |
LAION-Box-Emotional-v0.7-r128_best2_step1650.safetensors |
1650 | 0.205 |
LAION-Box-Emotional-v0.7-r128_best3_step350.safetensors |
350 | 0.208 |
dramabox-audio-components.safetensors |
β | VAE + vocoder (from ResembleAI/Dramabox, ~1.9 GB) |
Recommended: best1_step100. Also inference.py, download_components.py.
Components needed for inference
- audio DiT β this repo's
*Emotional*.safetensors(β included) - VAE + vocoder β
dramabox-audio-components.safetensors(β included) - text/prompt encoder β
unsloth/gemma-3-12b-it-bnb-4bit(Google Gemma 3 12B, ~7.4 GB) βdownload_components.py - reference denoiser β
nvidia/RE-USE(SEMamba) βdownload_components.py - pipeline code β DramaBox / LTX-2.3 (
ltx2+src/) fromResembleAI/Dramabox
Google Gemma + NVIDIA RE-USE are fetched from their canonical repos (not re-hosted), under their own licenses.
Usage
import sys; sys.path.insert(0, "DramaBox/src")
from inference_server import TTSServer
tts = TTSServer(checkpoint="LAION-Box-Emotional-v0.7-r128_best1_step100.safetensors",
full_checkpoint="dramabox-audio-components.safetensors",
gemma_root="<gemma dir>", device="cuda", dtype="bf16", bnb_4bit=True)
tts.generate_to_file(prompt="A woman, voice breaking: 'You finally came back.'",
output="out.wav", voice_ref="reference_voice.wav",
cfg_scale=2.5, stg_scale=1.5, denoise_ref=True, seed=42)
Put the emotional direction in the prompt (e.g. "furious, shouting", "tender and hushed").
cfg_scale β = follows the emotional prompt harder.
Training
rank 128, Ξ± 128, lr 1e-4, 6Γ GPU, grad-accum 8, bf16, 10 epochs on the 5,596-sample high-emotion
subset (top-10%/30% by EmoNet intensity via laion/Empathic-Insight-Voice-Plus), mixed with ~35 %
freshly-streamed German (β3,000 new, non-repeating Emolia German samples per emotional epoch, generated
live by a Gemma producer) so German quality is retained. Best-3 by flow-matching loss.
Emotional data: TTS-AGI/emotional-voice-acting-subset-v0.7 (private).
Credits & license
LTX-2.3 Β© Lightricks (LTX-2 Community License) Β· DramaBox Β© Resemble AI Β· Gemma Β© Google Β· RE-USE Β© NVIDIA. Emotional fine-tune by LAION. Research/eval use.