Update app.py

app.py

@@ -139,53 +139,73 @@ def get_license(models: list[pd.Series]) -> str:
 
 
 def create_config(models: list[pd.Series]) -> str:
-    slerp_config = f"""
-slices:
-  - sources:
-      - model: {models[0]["Model"]}
-        layer_range: [0, 32]
-      - model: {models[1]["Model"]}
-        layer_range: [0, 32]
-merge_method: slerp
-base_model: {models[0]["Model"]}
-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
-random_seed: 0
-    """
-    dare_config = f"""
+    slerp_config = """
 models:
-- model: mlabonne/Meta-Llama-3-8B
-  # No parameters necessary for base model
-- model: {models[0]["Model"]}
-  parameters:
-    density: 0.53
-    weight: 0.5
-- model: {models[1]["Model"]}
-  parameters:
-    density: 0.53
-    weight: 0.5
+  - model: NousResearch/Meta-Llama-3-8B
+    # No parameters necessary for base model
+  - model: NousResearch/Meta-Llama-3-8B-Instruct
+    parameters:
+      density: 0.6
+      weight: 0.5
+  - model: mlabonne/OrpoLlama-3-8B
+    parameters:
+      density: 0.55
+      weight: 0.05
 merge_method: dare_ties
-base_model: mlabonne/Meta-Llama-3-8B
+base_model: NousResearch/Meta-Llama-3-8B
 parameters:
-int8_mask: true
-dtype: bfloat16
-random_seed: 0
-""" 
-    stock_config = f"""
-models:
-  - model: mlabonne/Meta-Llama-3-8B
-  - model: {models[0]["Model"]}
-  - model: {models[1]["Model"]}
-merge_method: model_stock
-base_model: mlabonne/Meta-Llama-3-8B
-dtype: bfloat16    
+  int8_mask: true
+dtype: float16
 """
+    dare_config = slerp_config
+    stock_config = slerp_config
+#     slerp_config = f"""
+# slices:
+#   - sources:
+#       - model: {models[0]["Model"]}
+#         layer_range: [0, 32]
+#       - model: {models[1]["Model"]}
+#         layer_range: [0, 32]
+# merge_method: slerp
+# base_model: {models[0]["Model"]}
+# 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
+# random_seed: 0
+#     """
+#     dare_config = f"""
+# models:
+# - model: mlabonne/Meta-Llama-3-8B
+#   # No parameters necessary for base model
+# - model: {models[0]["Model"]}
+#   parameters:
+#     density: 0.53
+#     weight: 0.5
+# - model: {models[1]["Model"]}
+#   parameters:
+#     density: 0.53
+#     weight: 0.5
+# merge_method: dare_ties
+# base_model: mlabonne/Meta-Llama-3-8B
+# parameters:
+# int8_mask: true
+# dtype: bfloat16
+# random_seed: 0
+# """ 
+#     stock_config = f"""
+# models:
+#   - model: mlabonne/Meta-Llama-3-8B
+#   - model: {models[0]["Model"]}
+#   - model: {models[1]["Model"]}
+# merge_method: model_stock
+# base_model: mlabonne/Meta-Llama-3-8B
+# dtype: bfloat16    
+# """
     yaml_config = random.choices([slerp_config, dare_config, stock_config], weights=[0.5, 0.4, 0.1], k=1)[0]
 
     with open('config.yaml', 'w', encoding="utf-8") as f: