calcuis/wan-1.3b-gguf

gguf quantized version of wan 1.3b models

• drag wan to > ./ComfyUI/models/diffusion_models
• drag umt5 to > ./ComfyUI/models/text_encoders
• drag pig to > ./ComfyUI/models/vae

  

  Prompt

  a pig moving quickly in a beautiful winter scenery nature trees sunset tracking camera

  Negative Prompt

  blurry ugly bad

  

  Prompt

  a pig moving quickly in a beautiful winter scenery nature trees sunset tracking camera

  Negative Prompt

  blurry ugly bad

  

  Prompt

  a pig moving quickly in a beautiful winter scenery nature trees sunset tracking camera

  Negative Prompt

  blurry ugly bad

  

  Prompt

  a pig moving quickly in a beautiful winter scenery nature trees sunset tracking camera

  Negative Prompt

  blurry ugly bad

  

  Prompt

  a pig moving quickly in a beautiful winter scenery nature trees sunset tracking camera

  Negative Prompt

  blurry ugly bad

  

  Prompt

  a pig moving quickly in a beautiful winter scenery nature trees sunset tracking camera

  Negative Prompt

  blurry ugly bad

review

• wan architecture; should work on both comfyui-gguf and gguf nodes
• full set gguf works right away (model + encoder + vae); gguf node is recommended for full gguf
• vace model is recommended, since it doesn't need vision clip to work (for i2v and v2v) and run faster than fun model a lot, according to the initial test results
• upgrade your node for umt5 gguf encoder support
• note: for umt5 gguf, you might encounter oom after rebuilding your tokenizer in the first prompt (once built the tokenizer alive during the session; before you kill it); don't panic, prompt again it should work

reference

• base model from wan-ai
• comfyui from comfyanonymous
• comfyui-gguf city96 (special thanks; fully compatible)
• pig architecture from connector
• gguf-node (pypi|repo|pack)