updating README

README.md

@@ -128,7 +128,8 @@ A quick overview of the currently supported merge methods:
 | [Model Breadcrumbs](https://arxiv.org/abs/2312.06795)                                            | `breadcrumbs`        | ✅          | ✅              |
 | [Model Breadcrumbs](https://arxiv.org/abs/2312.06795) + [TIES](https://arxiv.org/abs/2306.01708) | `breadcrumbs_ties`   | ✅          | ✅              |
 | [Model Stock](https://arxiv.org/abs/2403.19522)                                                  | `model_stock`        | ✅          | ✅              |
-
+| [DELLA](https://arxiv.org/abs/2406.11617)                                                  | `della`        | ✅          | ✅              |
+| [DELLA](https://arxiv.org/abs/2406.11617) [Task Arithmetic](https://arxiv.org/abs/2212.04089)                                                  | `della_linear`        | ✅          | ✅              |
 ### Linear
 
 The classic merge method - a simple weighted average.
@@ -189,6 +190,15 @@ Parameters:
 
 - `filter_wise`: if true, weight calculation will be per-row rather than per-tensor. Not recommended.
 
+### [DELLA](https://arxiv.org/abs/2406.11617)
+
+Building upon DARE, DELLA uses adaptive pruning based on parameter magnitudes. DELLA first ranks parameters in each row of delta parameters and assigns drop probabilities inversely proportional to their magnitudes. This allows it to retain more important changes while reducing interference. After pruning, it rescales the remaining parameters similar to [DARE](#dare). DELLA can be used with (`della`) or without (`della_linear`) the sign elect step of TIES
+
+Parameters: same as [Linear](#linear), plus:
+- `density` - fraction of weights in differences from the base model to retain
+- `epsilon` - maximum change in drop probability based on magnitude. Drop probabilities assigned will range from `density - epsilon` to `density + epsilon`. (When selecting values for `density` and `epsilon`, ensure that the range of probabilities falls within 0 to 1)
+- `lambda` - scaling factor for the final merged delta parameters before merging with the base parameters.
+
 ## LoRA extraction
 
 Mergekit allows extracting PEFT-compatible low-rank approximations of finetuned models.