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README.md

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+---
+license: apache-2.0
+tags:
+- merge
+- mergekit
+- lazymergekit
+- codellama/CodeLlama-7b-Python-hf
+- NousResearch/Llama-2-7b-chat-hf
+---
+
+# my-merged-model
+
+my-merged-model is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
+* [codellama/CodeLlama-7b-Python-hf](https://huggingface.co/codellama/CodeLlama-7b-Python-hf)
+* [NousResearch/Llama-2-7b-chat-hf](https://huggingface.co/NousResearch/Llama-2-7b-chat-hf)
+
+## 🧩 Configuration
+
+```yaml
+slices:
+  - sources:
+      - model: codellama/CodeLlama-7b-Python-hf
+        layer_range: [0, 32]
+      - model: NousResearch/Llama-2-7b-chat-hf
+        layer_range: [0, 32]
+merge_method: slerp
+base_model: codellama/CodeLlama-7b-Python-hf
+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
+
+```

added_tokens.json

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+{
+  "▁<EOT>": 32003,
+  "▁<MID>": 32001,
+  "▁<PRE>": 32000,
+  "▁<SUF>": 32002
+}

config.json

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+{
+  "_name_or_path": "codellama/CodeLlama-7b-Python-hf",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "max_position_embeddings": 16384,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 32,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 1000000,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.38.1",
+  "use_cache": true,
+  "vocab_size": 32000
+}

mergekit_config.yml

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+
+slices:
+  - sources:
+      - model: codellama/CodeLlama-7b-Python-hf
+        layer_range: [0, 32]
+      - model: NousResearch/Llama-2-7b-chat-hf
+        layer_range: [0, 32]
+merge_method: slerp
+base_model: codellama/CodeLlama-7b-Python-hf
+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
+

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+    "▁<EOT>"
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+      "content": "▁<EOT>",
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+    "▁<EOT>"
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+  "eot_token": "▁<EOT>",
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