Create a Model Merging docs page.

docs/guides/model_merge.md

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+# Model Merging
+
+`invoke-training` provides utility scripts for several common model merging workflows. This page contains a summary of the available tools.
+
+## `extract_lora_from_model_diff.py`
+
+Extract a LoRA model that represents the difference between two base models.
+
+Note that the extracted LoRA model is a lossy representation of the difference between the models, so some degradation in quality is expected.
+
+For usage docs, run:
+```bash
+python src/invoke_training/model_merge/scripts/extract_lora_from_model_diff.py -h
+```
+
+## `merge_lora_into_model.py`
+
+Merge a LoRA model into a base model to produce a new base model.
+
+For usage docs, run:
+```bash
+python src/invoke_training/model_merge/scripts/merge_lora_into_model.py -h
+```
+
+## `merge_models.py`
+
+Merge 2 or more base models to produce a single base model (using either LERP or SLERP). This is a simple merge strategy that merges all model weights in the same way.
+
+For usage docs, run:
+```bash
+python src/invoke_training/model_merge/scripts/merge_models.py -h
+```
+
+## `merge_task_models_to_base_model.py`
+
+Merge 1 or more task-specific base models into a single starting base model (using either [TIES](https://arxiv.org/abs/2306.01708) or [DARE](https://arxiv.org/abs/2311.03099)). This merge strategy aims to preserve the task-specific behaviors of the task models while making only small changes to the original base model. This approach enables multiple task models to be merged without excessive interference between them.
+
+If you want to merge a task-specific LoRA into a base model using this strategy, first use `merge_lora_into_model.py` to produce a task-specific base model, then merge that new base model using this strategy.
+
+For usage docs, run:
+```bash
+python src/invoke_training/model_merge/scripts/merge_task_models_to_base_model.py -h
+```