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---
license: apache-2.0
base_model: Wan-AI/Wan2.2-TI2V-5B-Diffusers
pipeline_tag: text-to-video
library_name: mlx-gen
tags:
- mlx
- mlx-gen
- mflux
- apple-silicon
- 8-bit
- wan
- wan2.2
- video-generation
- text-to-video
- image-to-video
---
# wan2.2-ti2v-5b-diffusers-8bit
This repository contains MLX-Gen saved weights for `Wan-AI/Wan2.2-TI2V-5B-Diffusers`. The checkpoint is designed for local Apple Silicon inference with [`mlx-gen`](https://github.com/lpalbou/mlx-gen).
It uses the mflux/MLX saved-weight layout and MLX quantization tensors. It is not a Diffusers or Transformers `from_pretrained()` checkpoint.
## Source Model
Original model: [`Wan-AI/Wan2.2-TI2V-5B-Diffusers`](https://huggingface.co/Wan-AI/Wan2.2-TI2V-5B-Diffusers).
## License and Access
This quantized derivative follows the Apache 2.0 license of the source model.
## Quantization
This is an MLX q8 checkpoint for Wan2.2 TI2V. MLX-Gen uses 8-bit quantization for Wan modules where MLX supports quantization:
- q8 for quantizable Wan transformer modules.
- q8 for quantizable Wan VAE modules.
- BF16 for the UMT5 text encoder, scheduler metadata, tokenizer files, norms, and other non-quantizable parameters.
Wan q4 quality and any possible mixed q4/q8 policy are still under validation. Prefer q8 for publishable Wan checkpoints until the q4 policy is documented.
See the [MLX-Gen quantization docs](https://github.com/lpalbou/mlx-gen/blob/main/docs/quantization.md) for compatibility notes.
## Compatibility
Requires `mlx-gen >= 0.18.6`.
Generated with `mlx-gen 0.18.6`.
Use the `mlxgen` command and Python import path for new MLX-Gen projects.
## Usage
```bash
python -m pip install -U mlx-gen
mlxgen download --model AbstractFramework/wan2.2-ti2v-5b-diffusers-8bit
mlxgen generate \
--model AbstractFramework/wan2.2-ti2v-5b-diffusers-8bit \
--task text-to-video \
--prompt "Your video prompt here" \
--width 1280 \
--height 704 \
--frames 121 \
--steps 50 \
--guidance 5 \
--fps 24 \
--seed 42 \
--output video.mp4
```
## Attribution
MLX-Gen is based on [mflux](https://github.com/filipstrand/mflux) by Filip Strand and the original mflux contributors. This model card is generated by MLX-Gen so derived checkpoints keep that attribution visible.
Quantized and contributed by [@lpalbou](https://huggingface.co/lpalbou).