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README.md

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+---
+license: apache-2.0
+tags:
+- merge
+- mergekit
+- lazymergekit
+- meta-math/MetaMath-Mistral-7B
+- mistralai/Mistral-7B-v0.1
+- EmbeddedLLM/Mistral-7B-Merge-14-v0.2
+---
+
+# mathexpert7b
+
+mathexpert7b is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
+* [meta-math/MetaMath-Mistral-7B](https://huggingface.co/meta-math/MetaMath-Mistral-7B)
+* [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
+* [EmbeddedLLM/Mistral-7B-Merge-14-v0.2](https://huggingface.co/EmbeddedLLM/Mistral-7B-Merge-14-v0.2)
+
+## 🧩 Configuration
+
+```yaml
+models:
+  - model: mistralai/Mistral-7B-v0.1
+    # No parameters necessary for base model
+  - model: meta-math/MetaMath-Mistral-7B
+    parameters:
+      density: 0.53
+      weight: 0.4
+  - model: mistralai/Mistral-7B-v0.1
+    parameters:
+      density: 0.53
+      weight: 0.3
+  - model: EmbeddedLLM/Mistral-7B-Merge-14-v0.2
+    parameters:
+      density: 0.53
+      weight: 0.3
+merge_method: dare_ties
+base_model: mistralai/Mistral-7B-v0.1
+parameters:
+  int8_mask: true
+dtype: bfloat16
+
+```

config.json

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+{
+  "_name_or_path": "mistralai/Mistral-7B-v0.1",
+  "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": "4.38.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}

mergekit_config.yml

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+
+models:
+  - model: mistralai/Mistral-7B-v0.1
+    # No parameters necessary for base model
+  - model: meta-math/MetaMath-Mistral-7B
+    parameters:
+      density: 0.53
+      weight: 0.4
+  - model: mistralai/Mistral-7B-v0.1
+    parameters:
+      density: 0.53
+      weight: 0.3
+  - model: EmbeddedLLM/Mistral-7B-Merge-14-v0.2
+    parameters:
+      density: 0.53
+      weight: 0.3
+merge_method: dare_ties
+base_model: mistralai/Mistral-7B-v0.1
+parameters:
+  int8_mask: true
+dtype: bfloat16
+

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