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Includes 30 custom nodes committed directly, 7 Civitai-exclusive loras stored via Git LFS, and a setup script that installs all dependencies and downloads HuggingFace-hosted models on vast.ai. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
122 lines
3.3 KiB
Markdown
122 lines
3.3 KiB
Markdown
# Guide
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# Installing
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First of all, you should install ComfyUI and [ComfyUI Manager](https://github.com/ltdrdata/ComfyUI-Manager).
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After that, launch ComfUI.
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In the right panel you can find “Manager” button, click on.
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You will see big window, click on “Custom Nodes Manager”.
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Go to search field, and start typing “x-flux-comfyui”,
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Click “install” button.
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Now, you have access to X-Labs nodes, you can find it in “XLabsNodes” category.
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# Flux Installing
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There is complete guide by Comfyanonimus [Guide](https://comfyanonymous.github.io/ComfyUI_examples/flux/)
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Important! You should use flux dev, not schnell, if your computer is capable of this, it is better to use fp8 or bf16 (default).
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# Nodes
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## XLabs Sampler:
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Node inputs:
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model: get FLUX diffusion model (from unet loader)
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conditioning & neg_conditioning: input prompts after T5 and clip models (clip only allowed, but you should know, that you will not utilize about 40% of flux power, so use dual text node)
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latent_image: latent input for flux, may be empty latent or encoded with FLUX AE (VAE Encode) image (for image-to-image using)
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controlnet_condition: input for XLabs-AI ControlNet conditioning
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Output:
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latent: FLUX latent image, should be decoded with VAE Decoder to get image
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Parameters:
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noise_seed, control_after_generate: controls random generator
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steps: how many denoise steps will diffusion go
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timestep_to_start_cfg: how many steps diffusion will do before start to use negative sampling and cfg
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true_gs: true cfg scale, will be used after first “**timestep_to_start_cfg” steps**
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image_to_image_strength: how much will the original image affect to the output
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denoise_strength: how many noise will remain
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## Load Flux LoRA
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Gets flux model on input and outputs model modified with XLabs LoRA (strength of LoRA and name are selected by the parameters)
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## Load Flux ControlNet
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Gets controlnet name and returns flux controlnet.
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## Apply Flux ControlNet
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Gets controlnet, image and strength as parameter. Returns controlnet condition for XLabs Sampler.
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## Load Flux IPAdapter
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Gets IP Adapter name, CLIP ViT model and on which device it will work. Choose CUDA only if you have enough VRAM. Return Flux IPAdapter.
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## Apply Flux IPAdapter
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Gets FLUX model, IP Adapter and image. Returns modified model. Strength of IP Adapter comes from parameter.
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## Apply Advanced IPAdatper
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Like common one, but has more strength parameters.
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# Models
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We use custom folder for LoRAs, ControlNets and IPAdapters, the folders contains in `models\xlabs`.
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LoRAs goes to `ComfyUI\xlabs\loras`.
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ControlNets goes to `ComfyUI\xlabs\controlnets`.
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IPAdapters goes to `ComfyUI\xlabs\ipadapters`.
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An IPAdapter requires a CLIP VIT. We currently use Open-AI Clip ViT Large. You can find it here.
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[CLIP ViT model](https://huggingface.co/openai/clip-vit-large-patch14).
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Download model.safetensors, rename it as you want to (but .safetensors is required). And put it to `ComfyUI\models\clip-vision\`.
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