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README.md

@@ -3,38 +3,46 @@ tags:
 - merge
 - mergekit
 - lazymergekit
-- OpenPipe/mistral-ft-optimized-1218
-- mlabonne/NeuralHermes-2.5-Mistral-7B
+- AI-Sweden-Models/tyr
+- mlabonne/NeuralBeagle14-7B
+- neph1/bellman-7b-mistral-instruct-v0.2
 base_model:
-- OpenPipe/mistral-ft-optimized-1218
-- mlabonne/NeuralHermes-2.5-Mistral-7B
+- AI-Sweden-Models/tyr
+- mlabonne/NeuralBeagle14-7B
+- neph1/bellman-7b-mistral-instruct-v0.2
 ---
 
 # NeuralPipe-7B-slerp
 
 NeuralPipe-7B-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
-* [OpenPipe/mistral-ft-optimized-1218](https://huggingface.co/OpenPipe/mistral-ft-optimized-1218)
-* [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B)
+* [AI-Sweden-Models/tyr](https://huggingface.co/AI-Sweden-Models/tyr)
+* [mlabonne/NeuralBeagle14-7B](https://huggingface.co/mlabonne/NeuralBeagle14-7B)
+* [neph1/bellman-7b-mistral-instruct-v0.2](https://huggingface.co/neph1/bellman-7b-mistral-instruct-v0.2)
 
 ## 🧩 Configuration
 
 ```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
+models:
+  - model: Nexusflow/Starling-LM-7B-beta
+    # No parameters necessary for base model
+  - model: AI-Sweden-Models/tyr
+    parameters:
+      density: 0.53
+      weight: 0.4
+  - model: mlabonne/NeuralBeagle14-7B
+    parameters:
+      density: 0.53
+      weight: 0.3
+  - model: neph1/bellman-7b-mistral-instruct-v0.2
+    parameters:
+      density: 0.53
+      weight: 0.3
+merge_method: dare_ties
+base_model: Nexusflow/Starling-LM-7B-beta
 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
+  int8_mask: true
 dtype: bfloat16
+
 ```
 
 ## 💻 Usage
@@ -46,7 +54,7 @@ from transformers import AutoTokenizer
 import transformers
 import torch
 
-model = "Knobi3/NeuralPipe-7B-slerp"
+model = "knobi3/NeuralPipe-7B-slerp"
 messages = [{"role": "user", "content": "What is a large language model?"}]
 
 tokenizer = AutoTokenizer.from_pretrained(model)