Table of Content
- Description
- ⛏️ CR Model Merge Stack:
- ⛏️ CR Model Merge Stack Input Parameters:
- ⛏️ CR Model Merge Stack Output Parameters:
- ⛏️ CR Model Merge Stack Usage Tips:
- ⛏️ CR Model Merge Stack Common Errors and Solutions:
- Related Nodes
ComfyUI Node: ⛏️ CR Model Merge Stack
Class Name
CR Model Merge Stack
Category 🧩 Comfyroll Studio/✨ Essential/⛏️ Model Merge
Author Suzie1 (Account age: 2158days)Extension Comfyroll StudioLatest Updated 2024-06-05Github Stars 0.49K
Github Ask Suzie1 Questions Current Questions Past Questions
How to Install Comfyroll Studio
Install this extension via the ComfyUI Manager by searching for Comfyroll Studio
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- Click the Manager button in the main menu
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- Select Custom Nodes Manager button
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- Enter Comfyroll Studio in the search bar
After installation, click the Restart button to restart ComfyUI. Then, manually refresh your browser to clear the cache and access the updated list of nodes.
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⛏️ CR Model Merge Stack Description
Merge multiple AI models into a cohesive composite model with flexible stacking and merging methods for enhanced performance.
⛏️ CR Model Merge Stack:
The CR Model Merge Stack node is designed to facilitate the merging of multiple AI models into a single cohesive model. This node allows you to stack and merge different models using various methods, providing flexibility and control over the merging process. By leveraging this node, you can create a composite model that combines the strengths of individual models, potentially enhancing the overall performance and capabilities of your AI system. The node supports recursive merging, ensuring that the ratios of the models are applied correctly, and offers options for normalizing these ratios to maintain balance. This functionality is particularly useful for AI artists looking to blend different styles or features from multiple models into a single output.
⛏️ CR Model Merge Stack Input Parameters:
model_stack
This parameter represents the list of models to be merged. Each entry in the stack includes the model name, model ratio, and CLIP ratio. The model stack is essential for defining which models will be combined and in what proportions. The ratios determine the influence of each model in the final merged output. There is no strict minimum or maximum number of models, but at least two models are typically needed for merging. The default value is an empty list.
merge_method
This parameter specifies the method used for merging the models. The available options include "Weighted" and potentially other methods. The merge method impacts how the ratios are applied during the merging process. For example, the "Weighted" method adjusts the ratios to give more weight to certain models. The default value is "Weighted".
normalise_ratios
This parameter indicates whether the model and CLIP ratios should be normalized. Normalizing the ratios ensures that their sum equals one, maintaining balance in the merged model. The options are "Yes" or "No". If set to "Yes", the node will automatically adjust the ratios to sum to one. The default value is "No".
weight_factor
This parameter is used in the "Weighted" merge method to adjust the weight assigned to the second model. It allows for fine-tuning the influence of the second model in the merged output. The weight factor is a float value between 0 and 1, with the default value typically being 0.5.
⛏️ CR Model Merge Stack Output Parameters:
MODEL_STACK
This output parameter provides the final merged model stack. It includes the combined model and its associated information, such as the applied ratios and the method used for merging. This output is crucial for understanding the composition of the merged model and for further processing or analysis.
show_help
This output parameter provides a URL link to the documentation or help page for the CR Model Merge Stack node. It is useful for users who need additional information or guidance on using the node effectively. The link directs to a detailed wiki page that explains the node's functionality and usage.
⛏️ CR Model Merge Stack Usage Tips:
- Ensure that the model ratios and CLIP ratios are set appropriately to achieve the desired balance in the merged model.
- Use the "Weighted" merge method to give more influence to specific models by adjusting the weight factor.
- Normalize the ratios if you want to maintain a balanced influence of all models in the final output.
- Refer to the provided help link for detailed instructions and examples on using the node effectively.
⛏️ CR Model Merge Stack Common Errors and Solutions:
[Warning] Apply Model Merge: No active models selected in the model merge stack
- Explanation : This error occurs when no models are provided in the model stack.
- Solution : Ensure that you have added at least two models to the model stack before attempting to merge.
[Warning] Apply Model Merge: Only one active model found in the model merge stack. At least 2 models are normally needed for merging. The active model will be output.
- Explanation : This warning indicates that only one model is present in the stack, which is insufficient for merging.
- Solution : Add more models to the model stack to proceed with the merging process.
[Warning] Apply Model Merge: Sum of model ratios != 1. Ratios will be normalised
- Explanation : This warning appears when the sum of the model ratios does not equal one, and normalization is required.
- Solution : Either manually adjust the ratios to sum to one or enable the normalization option to let the node handle it automatically.
