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Remove Wan2 model files, including configuration, attention mechanisms, and utility functions, to streamline the codebase and eliminate unused components. This cleanup enhances maintainability and focuses on the core functionality of the Wan2 module.

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Prince Canuma
2026-03-18 17:59:43 +01:00
parent b029668cd2
commit 996a542011
37 changed files with 354 additions and 354 deletions
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12
README.md
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@@ -93,18 +93,18 @@ Both [Wan2.1](https://github.com/Wan-Video/Wan2.1) and [Wan2.2](https://github.c
### Step 0: Download and Convert Weights
See the dedicated Wan2.1/Wan2.2 [README.md](mlx_video/models/wan/README.md) for details.
See the dedicated Wan2.1/Wan2.2 [README.md](mlx_video/models/wan_2/README.md) for details.
### Step 1: Generate Video
```bash
# Wan2.1 — uses defaults from config (50 steps, shift=5.0, guide=5.0)
python -m mlx_video.wan2.generate \
python -m mlx_video.wan_2.generate \
--model-dir wan21_mlx \
--prompt "A cat playing piano in a cozy room"
# Wan2.2 — uses defaults from config (40 steps, shift=12.0, guide=3.0,4.0)
python -m mlx_video.wan2.generate \
python -m mlx_video.wan_2.generate \
--model-dir wan22_mlx \
--prompt "A cat playing piano in a cozy room"
```
@@ -112,7 +112,7 @@ python -m mlx_video.wan2.generate \
With custom settings:
```bash
python -m mlx_video.wan2.generate \
python -m mlx_video.wan_2.generate \
--model-dir wan21_mlx \
--prompt "Ocean waves at sunset, cinematic, 4K" \
--negative-prompt "blurry, low quality" \
@@ -131,7 +131,7 @@ The pipeline auto-detects the model version from `config.json` and selects the r
### Image-to-Video (I2V-14B)
```bash
python -m mlx_video.wan2.generate \
python -m mlx_video.wan_2.generate \
--model-dir wan22_i2v_mlx \
--prompt "The camera slowly zooms in as the subject begins to move" \
--image start.png \
@@ -146,7 +146,7 @@ LoRAs can be used with the `--lora-high` and `--lora-low` command line switches.
For example, using the distilled [Wan2.2-Lightning](https://huggingface.co/lightx2v/Wan2.2-Lightning) LoRA for 4-step generation:
```bash
python -m mlx_vide.wan2.generate \
python -m mlx_video.wan_2.generate \
--model-dir /Volumes/SSD/Wan-AI/Wan2.2-T2V-A14B-MLX \
--width 480 \
--height 704 \