GGUF quantized and fp8 scaled version of hyvid with lora anime adapter
setup (once)
- drag hyvid_lora_adapter.safetensors [323MB] to > ./ComfyUI/models/loras
- drag hunyuan-video-t2v-720p-q4_0.gguf [7.74GB] to > ./ComfyUI/models/diffusion_models
- drag llava_llama3-q4_0.gguf [4.68GB] to > ./ComfyUI/models/text_encoders
- drag clip_l_fp8_e4m3fn.safetensors [123MB] to > ./ComfyUI/models/text_encoders
- drag hunyuan_video_vae_fp8_e4m3fn.safetensors [247MB] to > ./ComfyUI/models/vae
run it straight (no installation needed way)
- run the .bat file in the main directory (assuming you are using the gguf-node pack below)
- drag the demo clip or the workflow json file (below) to > your browser
workflows
- example workflow for gguf (upgrade your node for llava gguf support; more quantized llava-llama3 version here)
- example workflow for safetensors (fp8 scaled version [13.2GB] is recommended)
review
- more stable output if adapter applied
- working good even with fp8_e4m3fn scaled clip and vae
- significant changes in loading speed while using the new quantized/scaled file(s) with revised workflow (see above)
references
- lora adapter from trojblue
- base model from tencent
- fast model from fastvideo
- comfyui from comfyanonymous
- comfyui-gguf city96
- gguf-comfy pack
- gguf-node (pypi|repo|pack)