VTM-Elf 0.01
Pose-conditioned character generation for VTuber pipelines.
Status: beta · Platform: Windows + NVIDIA CUDA only
Architecture
- Dual-stream DiT-30M (pose + identity in one backbone)
- Pose from keypoints; identity from a reference image
- Rectified flow + SD VAE @ 768×768
- Checkpoint:
VTM-elf.pt-000060000(~436 MB, step 60k)
Measured latency
| Hardware | Resolution | Observed rate |
|---|---|---|
| RTX 5060 Ti | 768×768 | ~7 FPS |
Data
Training used a small private character set:
- ~1,500 characters
- ~16–30 images per character
Generation quality in this release is limited mainly by model capacity (DiT-30M) and dataset scale.
Getting started
Requirements
- Windows
- NVIDIA GPU + CUDA
- Other OS / AMD / CPU: not supported in this release
Download
hf download sinBoo1/VTM-Elf-0.01 VTM-elf.pt-000060000 --local-dir ./VTM-Elf-0.01
from huggingface_hub import hf_hub_download
ckpt = hf_hub_download(
repo_id="sinBoo1/VTM-Elf-0.01",
filename="VTM-elf.pt-000060000",
)
Files
| File | Description |
|---|---|
VTM-elf.pt-000060000 |
DiT-30M weights (step 60k) |
README.md |
This card |
Runtime code for live camera → keypoints → inference is separate from this weight repo.
Limitations
- Beta: soft detail, identity drift, and pose errors are common
- Small data + DiT-30M capacity constrain image quality
- ~7 FPS on RTX 5060 Ti at 768
- Windows + CUDA only
- Framing: torso-up only (roughly head → mid-torso). Legs / most of the waist are not supported
- Hands: not supported
- Character types not supported: realistic humans; non-humanoid / furries
- Accessories: glasses and hats generally work; most other accessories are not supported
Intended use
Research and prototyping of VTuber pose → image pipelines (live drive, pose retarget experiments). Not a finished production renderer.