This GGUF file is a direct conversion of Wan-AI/Wan2.2-T2V-A14B Since this is a quantized model, all original licensing terms and usage restrictions remain in effect. Usage The model can be used with the ComfyUI custom node ComfyUI-GGUF by city96 Place model files in ComfyUI/models/unet see the GitHub readme for further installation instructions.
SMD-Wan2.1-1.3B is an open-weight model for text to video from Jiawei Zhang, released under Apache License 2.0. Its published files total 1.4 GB.
4-step SMD for video generation. The student adapters, standalone inference code and reproducible examples are included. Upstream base components are downloaded separately.
Parameters—
Context—
Weights1.4 GB
Licenseapache-2.0
AccessOpen weights
Monthly Downloads—
Model Card
By Jiawei Zhang, published under apache-2.0, revision 0d91bd06e0eb.
4-step SMD for video generation. The student adapters, standalone inference code and reproducible examples are included. Upstream base components are downloaded separately. Prompt: A small white delivery robot labeled "SMD" in large blue capital letters drives slowly along a bright hallway. The camera tracks alongside the robot, realistic motion, soft daylight. Use Linux, Python 3.12 and an NVIDIA GPU with CUDA support. The included inference code does not import the SMD training repository. The example was run on an A100 80 GB. Model CPU offload reduces GPU memory usage; enough host RAM is still needed to load the upstream components. Use --prompt, --seed and --output to generate another…
Read Jiawei Zhang's full model card
4-step SMD for video generation. The student adapters, standalone inference code and reproducible examples are included. Upstream base components are downloaded separately.
Training code · SMD collection
Example
Download the video
Prompt: A small white delivery robot labeled "SMD" in large blue capital letters drives slowly along a bright hallway. The camera tracks alongside the robot, realistic motion, soft daylight.
Seed: 1234. Size: 832 × 480. Frames: 81. FPS: 16.
Case settings · Generation receipt
Models
| Variant | Weights | Steps | Size |
|---|---|---|---|
| default | LoRA | 4 | 0.70 GB |
Run
Base: Wan-AI/Wan2.1-T2V-1.3B-Diffusers.
Use Linux, Python 3.12 and an NVIDIA GPU with CUDA support. The included inference code does not import the SMD training repository.
python3.12 -m venv .venv
source .venv/bin/activate
python -m pip install huggingface-hub
# Sign in to Hugging Face.
hf auth login
hf download zjwfufu/SMD-Wan2.1-1.3B --local-dir SMD-Wan2.1-1.3B --exclude 'lora/lora.safetensors'
cd SMD-Wan2.1-1.3B
python -m pip install -r requirements.txt
python infer.py --output outputs
The example was run on an A100 80 GB. Model CPU offload reduces GPU memory usage; enough host RAM is still needed to load the upstream components. Use --prompt, --seed and --output to generate another case. --base accepts a local upstream snapshot.
The student weights are published as smd_lora.safetensors at the repository root. The legacy lora/lora.safetensors remains available for existing integrations; the command above excludes that duplicate. The supplied loader prefers the root weight file and falls back to the legacy path. The adapter configuration, merge precision and sampling schedule are unchanged.
The first run downloads the upstream base components to the Hugging Face cache. Plan disk space for those components as well as the released weights; subsequent runs reuse the cache.
Sampling
The released sampler uses raw final-segment scale 0.3. The raw grid is built before the model-specific time shift. The included runner follows sampling.json; changing only an upstream pipeline's step count does not reproduce the student.
External classifier-free guidance is disabled for the students. Any embedded guidance remains specified in sampling.json.
The supplied loader validates and applies all LoRA matrices and saved replacement tensors, with the recorded merge precision. Omitting replacement tensors or using a different base can change the result.
License and attribution
Base components retain the terms described in the Wan-AI/Wan2.1-T2V-1.3B-Diffusers model card. Original code notices and bundled licenses are retained. Adapter use remains subject to the applicable base-model terms.
Identity and Version
- Repository
- zjwfufu/SMD-Wan2.1-1.3B
- Publisher
- Jiawei Zhang
- Task
- Text to video
- Modality
- Video
- Library
- diffusers
- Parameters
- Not stated by the source
- Languages
- en
- Revision
- 0d91bd06e0eb09ab2716ee10066797b14a34b7e6
- First published
- 2026-10-07
- Last updated
- 2026-10-16
Files and Weights
14 files, 1.4 GB in total. The weights are 2 files totalling 1.4 GB in safetensors.
Weights2 files · 1.4 GB
Configuration6 files · 11.7 KB
Documentation2 files · 15.0 KB
Other3 files · 581.0 KB
Repository1 file · 1.6 KB
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| lora/lora.safetensors | Weights | 700.8 MB | 817f70d95481 |
| smd_lora.safetensors | Weights | 700.8 MB | 817f70d95481 |
| examples/case.json | Configuration | 285 B | — |
| examples/generation.json | Configuration | 508 B | — |
| infer.py | Configuration | 4.2 KB | — |
| inference_utils.py | Configuration | 5.7 KB | — |
| lora/adapter_config.json | Configuration | 205 B | — |
| sampling.json | Configuration | 729 B | — |
| LICENSE-code | Documentation | 11.4 KB | — |
| README.md | Documentation | 3.6 KB | — |
| examples/poster.png | Other | 252.7 KB | af95ef760e66 |
| examples/sample.mp4 | Other | 328.1 KB | 8fd53493b9ed |
| requirements.txt | Other | 226 B | — |
| .gitattributes | Repository | 1.6 KB | — |
License and Download
- License
- apache-2.0
- Access
- Open weights, no gate
- Download size
- 1.4 GB
Download from Jiawei Zhang
Released by Jiawei Zhang through its official repository on Hugging Face. Read the license.
Built From
- Adapter of Wan-AI/Wan2.1-T2V-1.3B-Diffusers
- Derived from Wan-AI/Wan2.1-T2V-1.3B-Diffusers
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 1.4 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About SMD-Wan2.1-1.3B
Can I use SMD-Wan2.1-1.3B commercially?
Yes. SMD-Wan2.1-1.3B is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.
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