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README.md

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+---
+base_model:
+- mistralai/Mistral-7B-v0.1
+- PrunaAI/WizardLM-WizardMath-7B-V1.0-bnb-4bit-smashed
+- codellama/CodeLlama-7b-Instruct-hf
+library_name: transformers
+tags:
+- mergekit
+- merge
+
+---
+# output_folder merge
+
+This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
+
+## Merge Details
+### Merge Method
+
+This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) as a base.
+
+### Models Merged
+
+The following models were included in the merge:
+* [PrunaAI/WizardLM-WizardMath-7B-V1.0-bnb-4bit-smashed](https://huggingface.co/PrunaAI/WizardLM-WizardMath-7B-V1.0-bnb-4bit-smashed)
+* [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf)
+
+### Configuration
+
+The following YAML configuration was used to produce this model:
+
+```yaml
+models:
+  - model: mistralai/Mistral-7B-v0.1  # no parameters necessary for base model
+  - model: PrunaAI/WizardLM-WizardMath-7B-V1.0-bnb-4bit-smashed
+    parameters:
+      density: 0.5  # fraction of weights in differences from the base model to retain
+      weight:   # weight gradient
+        - filter: mlp
+          value: 0.5
+        - value: 0
+  - model: codellama/CodeLlama-7b-Instruct-hf
+    parameters:
+      density: 0.5
+      weight: 0.5
+merge_method: ties
+base_model: mistralai/Mistral-7B-v0.1
+parameters:
+  normalize: true
+  int8_mask: true
+dtype: float16
+```

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": "float16",
+  "transformers_version": "4.40.0",
+  "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: PrunaAI/WizardLM-WizardMath-7B-V1.0-bnb-4bit-smashed
+    parameters:
+      density: 0.5  # fraction of weights in differences from the base model to retain
+      weight:   # weight gradient
+        - filter: mlp
+          value: 0.5
+        - value: 0
+  - model: codellama/CodeLlama-7b-Instruct-hf
+    parameters:
+      density: 0.5
+      weight: 0.5
+merge_method: ties
+base_model: mistralai/Mistral-7B-v0.1
+parameters:
+  normalize: true
+  int8_mask: true
+dtype: float16

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