--- 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).