Linum-AI/linum-v2-360p

Linum v2 - 360p

Small text-to-video generation model trained from scratch by Linum AI. Lower VRAM requirements than the 720p variant. Read the launch blog post.

Model Description

Linum V2 is a 2B parameter Diffusion Transformer (DiT) based text-to-video model that generates 360p (640x360) videos at 24 FPS from text prompts.

Property	Value
Resolution	640x360 (360p)
Frame Rate	24 FPS
Duration	2-5 seconds
Parameters	2B
Architecture	DiT + T5-XXL + WAN 2.1 VAE

Quick Start

See the full documentation at: GitHub - Linum-AI/linum-v2

First, install uv:

curl -LsSf https://astral.sh/uv/install.sh | sh

Then clone and generate your first video:

git clone https://github.com/Linum-AI/linum-v2.git
cd linum-v2
uv sync
uv run python generate_video.py \
    --prompt "A cute 3D animated baby goat with shaggy gray fur, a fluffy white chin tuft, and stubby curved horns perches on a round wooden stool. Warm golden studio lights bounce off its glossy cherry-red acoustic guitar as it rhythmically strums with a confident hoof, hind legs dangling. Framed family portraits of other barnyard animals line the cream-colored walls, a leafy potted ficus sits in the back corner, and dust motes drift through the cozy, sun-speckled room." \
    --output goat.mp4 \
    --seed 16 \
    --cfg 10.0 \
    --resolution 360p

Weights are downloaded automatically on first run (~20GB).

For higher quality, use the 720p model (requires more VRAM).

Files

├── dit/
│   └── 360p.safetensors      # DiT model weights
├── vae/
│   └── vae.safetensors       # WAN 2.1 Video VAE
└── t5/
    ├── text_encoder/         # T5-XXL encoder
    └── tokenizer/            # T5 tokenizer

License

Apache 2.0

Citation

@software{linum_v2_2026,
  title = {Linum V2: Text-to-Video Generation},
  author = {Linum AI},
  year = {2026},
  url = {https://github.com/Linum-AI/linum-v2}
}