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README.md

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+---
+base_model:
+- v000000/MN-12B-Part1
+- v000000/MN-12B-Part2
+library_name: transformers
+tags:
+- mergekit
+- merge
+
+---
+# 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 SLERP merge method.
+
+### Models Merged
+
+The following models were included in the merge:
+* [v000000/MN-12B-Part1](https://huggingface.co/v000000/MN-12B-Part1)
+* [v000000/MN-12B-Part2](https://huggingface.co/v000000/MN-12B-Part2)
+
+### Configuration
+
+The following YAML configuration was used to produce this model:
+
+```yaml
+slices:
+  - sources:
+      - model: v000000/MN-12B-Part2
+        layer_range: [0, 40]
+      - model: v000000/MN-12B-Part1
+        layer_range: [0, 40]
+merge_method: slerp
+base_model: v000000/MN-12B-Part1
+parameters:
+  t:
+    - filter: self_attn
+      value: [0, 0.5, 0.3, 0.7, 0.6, 0.1, 0.6, 0.3, 0.8, 0.5]
+    - filter: mlp
+      value: [0, 0.5, 0.4, 0.3, 0, 0.3, 0.4, 0.7, 0.2, 0.5]
+    - value: 0.5
+dtype: bfloat16
+```

config.json

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+{
+  "_name_or_path": "v000000/MN-12B-Part1",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 1024000,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 40,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.44.0",
+  "use_cache": true,
+  "vocab_size": 131072
+}

mergekit_config.yml

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+slices:
+  - sources:
+      - model: v000000/MN-12B-Part2
+        layer_range: [0, 40]
+      - model: v000000/MN-12B-Part1
+        layer_range: [0, 40]
+merge_method: slerp
+base_model: v000000/MN-12B-Part1
+parameters:
+  t:
+    - filter: self_attn
+      value: [0, 0.5, 0.3, 0.7, 0.6, 0.1, 0.6, 0.3, 0.8, 0.5]
+    - filter: mlp
+      value: [0, 0.5, 0.4, 0.3, 0, 0.3, 0.4, 0.7, 0.2, 0.5]
+    - value: 0.5
+dtype: bfloat16

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