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+# Mistral-Merge-7B-slerp
+
+## Model Description
+The `Mistral-Merge-7B-slerp` is a merged model which leverages the spherical linear interpolation (SLERP) technique to blend layers from two distinct transformer-based models. This merging strategy is aimed at synthesizing a model that incorporates the robust linguistic capabilities of `OpenPipe/mistral-ft-optimized-1218` and the nuanced understanding of `mlabonne/NeuralHermes-2.5-Mistral-7B`.
+
+## Configuration
+The merging process was configured to apply a SLERP method across all comparable layers of the two source models. Below is the YAML configuration used for merging:
+
+```yaml
+slices:
+  - sources:
+      - model: OpenPipe/mistral-ft-optimized-1218
+        layer_range: [0, 32]
+      - model: mlabonne/NeuralHermes-2.5-Mistral-7B
+        layer_range: [0, 32]
+merge_method: slerp
+base_model: OpenPipe/mistral-ft-optimized-1218
+parameters:
+  t:
+    - filter: self_attn
+      value: [0, 0.5, 0.3, 0.7, 1]
+    - filter: mlp
+      value: [1, 0.5, 0.7, 0.3, 0]
+    - value: 0.5
+dtype: bfloat16
+```
+
+This configuration ensures that both self-attention and MLP (multi-layer perceptron) layers undergo interpolation with a gradient of weights to optimize the integration of features from both models.