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README.md

@@ -5,14 +5,17 @@ tags:
 - mergekit
 - lazymergekit
 - OpenPipe/mistral-ft-optimized-1218
+- mlabonne/NeuralHermes-2.5-Mistral-7B
 base_model:
 - OpenPipe/mistral-ft-optimized-1218
+- mlabonne/NeuralHermes-2.5-Mistral-7B
 ---
 
 # testing-slp
 
 testing-slp 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)
 
 ## 🧩 Configuration
 
@@ -29,7 +32,13 @@ slices:
     - 0
     - 32
     model: mlabonne/NeuralHermes-2.5-Mistral-7B
-```
+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```
 
 ## 💻 Usage
 

config.json

@@ -0,0 +1,26 @@
+{
+  "_name_or_path": "OpenPipe/mistral-ft-optimized-1218",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.39.3",
+  "use_cache": true,
+  "vocab_size": 32000
+}

mergekit_config.yml

@@ -0,0 +1,20 @@
+base_model: OpenPipe/mistral-ft-optimized-1218
+dtype: bfloat16
+merge_method: slerp
+slices:
+- sources:
+  - layer_range:
+    - 0
+    - 32
+    model: OpenPipe/mistral-ft-optimized-1218
+  - layer_range:
+    - 0
+    - 32
+    model: mlabonne/NeuralHermes-2.5-Mistral-7B
+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

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