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Model merging (and related functions) allow users to manipulate the model weights of various models without directly training the model. This functionality is supported in Invoke-training with scripts, but does not have direct Interface elements to interact with these capabilities.
Supported capabilities:
Base Model Merging: Selecting two models to merge the weights. This includes merging mechanisms like TIES/DARE (task models)
LoRA + Base Model Merging: Selecting N LoRAs to merge with a Base Model
Model Extraction: This selects a trained model, as well as a base model, and extracts the training as a LoRA.
Related scripts can be found in src/invoke_training/model_merge/scripts.
Users should have a new interface in addition to datasets/training that allows the user to leverage the above. The interface from the training tabs can be used as a base for UI layout/reference.
There are a lot of UX improvement opportunities generally across the training application (better template management, file path usage, etc.), which could be incorporated.
The text was updated successfully, but these errors were encountered:
Summary
Model merging (and related functions) allow users to manipulate the model weights of various models without directly training the model. This functionality is supported in Invoke-training with scripts, but does not have direct Interface elements to interact with these capabilities.
Supported capabilities:
Related scripts can be found in src/invoke_training/model_merge/scripts.
Users should have a new interface in addition to datasets/training that allows the user to leverage the above. The interface from the training tabs can be used as a base for UI layout/reference.
There are a lot of UX improvement opportunities generally across the training application (better template management, file path usage, etc.), which could be incorporated.
The text was updated successfully, but these errors were encountered: