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README.md

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+---
+base_model: []
+library_name: transformers
+tags:
+- mergekit
+- merge
+
+---
+# hanamixv3
+
+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:
+* ../L3.1-70B-Hanami-x1
+* ../Hermes-3-Llama-3.1-70B
+
+### Configuration
+
+The following YAML configuration was used to produce this model:
+
+```yaml
+slices:
+  - sources:
+    - model: ../Hermes-3-Llama-3.1-70B
+      layer_range: [0, 21] # 21
+    - model: ../L3.1-70B-Hanami-x1
+      layer_range: [0, 21]
+    parameters:
+      t: 0.2
+  - sources:
+    - model: ../L3.1-70B-Hanami-x1
+      layer_range: [16, 36] # 20
+    - model: ../Hermes-3-Llama-3.1-70B
+      layer_range: [16, 36]
+    parameters:
+      t: 0.8
+  - sources:
+    - model: ../Hermes-3-Llama-3.1-70B
+      layer_range: [30, 50] # 20
+    - model: ../L3.1-70B-Hanami-x1
+      layer_range: [30, 50]
+    parameters:
+      t: 0.2
+  - sources:
+    - model: ../L3.1-70B-Hanami-x1
+      layer_range: [40, 64] # 24
+    - model: ../Hermes-3-Llama-3.1-70B
+      layer_range: [40, 64]
+    parameters:
+      t: 0.8
+  - sources:
+    - model: ../Hermes-3-Llama-3.1-70B
+      layer_range: [60, 80] # 20
+    - model: ../L3.1-70B-Hanami-x1
+      layer_range: [60, 80]
+    parameters:
+      t: 0.2
+merge_method: slerp
+base_model: ../Hermes-3-Llama-3.1-70B
+idtype: bfloat16
+tokenizer_source: ../Hermes-3-Llama-3.1-70B
+
+```

config.json

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+{
+  "_name_or_path": "../Hermes-3-Llama-3.1-70B",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": 128039,
+  "hidden_act": "silu",
+  "hidden_size": 8192,
+  "initializer_range": 0.02,
+  "intermediate_size": 28672,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 64,
+  "num_hidden_layers": 105,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 8.0,
+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.44.2",
+  "use_cache": true,
+  "vocab_size": 128256
+}

mergekit_config.yml

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+slices:
+  - sources:
+    - model: ../Hermes-3-Llama-3.1-70B
+      layer_range: [0, 21] # 21
+    - model: ../L3.1-70B-Hanami-x1
+      layer_range: [0, 21]
+    parameters:
+      t: 0.2
+  - sources:
+    - model: ../L3.1-70B-Hanami-x1
+      layer_range: [16, 36] # 20
+    - model: ../Hermes-3-Llama-3.1-70B
+      layer_range: [16, 36]
+    parameters:
+      t: 0.8
+  - sources:
+    - model: ../Hermes-3-Llama-3.1-70B
+      layer_range: [30, 50] # 20
+    - model: ../L3.1-70B-Hanami-x1
+      layer_range: [30, 50]
+    parameters:
+      t: 0.2
+  - sources:
+    - model: ../L3.1-70B-Hanami-x1
+      layer_range: [40, 64] # 24
+    - model: ../Hermes-3-Llama-3.1-70B
+      layer_range: [40, 64]
+    parameters:
+      t: 0.8
+  - sources:
+    - model: ../Hermes-3-Llama-3.1-70B
+      layer_range: [60, 80] # 20
+    - model: ../L3.1-70B-Hanami-x1
+      layer_range: [60, 80]
+    parameters:
+      t: 0.2
+merge_method: slerp
+base_model: ../Hermes-3-Llama-3.1-70B
+idtype: bfloat16
+tokenizer_source: ../Hermes-3-Llama-3.1-70B

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special_tokens_map.json

@@ -0,0 +1,23 @@
+{
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+}

tokenizer_config.json

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+      "template": "{{bos_token}}{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}"
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+      "template": "{%- macro json_to_python_type(json_spec) %}\n{%- set basic_type_map = {\n    \"string\": \"str\",\n    \"number\": \"float\",\n    \"integer\": \"int\",\n    \"boolean\": \"bool\"\n} %}\n\n{%- if basic_type_map[json_spec.type] is defined %}\n    {{- basic_type_map[json_spec.type] }}\n{%- elif json_spec.type == \"array\" %}\n    {{- \"list[\" +  json_to_python_type(json_spec|items) + \"]\"}}\n{%- elif json_spec.type == \"object\" %}\n    {%- if json_spec.additionalProperties is defined %}\n        {{- \"dict[str, \" + json_to_python_type(json_spec.additionalProperties) + ']'}}\n    {%- else %}\n        {{- \"dict\" }}\n    {%- endif %}\n{%- elif json_spec.type is iterable %}\n    {{- \"Union[\" }}\n    {%- for t in json_spec.type %}\n      {{- json_to_python_type({\"type\": t}) }}\n      {%- if not loop.last %}\n        {{- \",\" }} \n    {%- endif %}\n    {%- endfor %}\n    {{- \"]\" }}\n{%- else %}\n    {{- \"Any\" }}\n{%- endif %}\n{%- endmacro %}\n\n\n{{- bos_token }}\n{{- \"You are a function calling AI model. You are provided with function signatures within <tools></tools> XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. Here are the available tools: <tools> \" }}\n{%- for tool in tools %}\n    {%- if tool.function is defined %}\n        {%- set tool = tool.function %}\n    {%- endif %}\n    {{- '{\"type\": \"function\", \"function\": ' }}\n    {{- '{\"name\": \"' + tool.name + '\", ' }}\n    {{- '\"description\": \"' + tool.name + '(' }}\n    {%- for param_name, param_fields in tool.parameters.properties|items %}\n        {{- param_name + \": \" + json_to_python_type(param_fields) }}\n        {%- if not loop.last %}\n            {{- \", \" }}\n        {%- endif %}\n    {%- endfor %}\n    {{- \")\" }}\n    {%- if tool.return is defined %}\n        {{- \" -> \" + json_to_python_type(tool.return) }}\n    {%- endif %}\n    {{- \" - \" + tool.description + \"\\n\\n\" }}\n    {%- for param_name, param_fields in tool.parameters.properties|items %}\n        {%- if loop.first %}\n            {{- \"    Args:\\n\" }}\n        {%- endif %}\n        {{- \"        \" + param_name + \"(\" + json_to_python_type(param_fields) + \"): \" + param_fields.description|trim }}\n    {%- endfor %}\n    {%- if tool.return is defined and tool.return.description is defined %}\n        {{- \"\\n    Returns:\\n        \" + tool.return.description }}\n    {%- endif %}\n    {{- '\"' }}\n    {{- ', \"parameters\": ' }}\n    {%- if tool.parameters.properties | length == 0 %}\n        {{- \"{}\" }}\n    {%- else %}\n        {{- tool.parameters|tojson }}\n    {%- endif %}\n    {{- \"}\" }}\n    {%- if not loop.last %}\n        {{- \"\\n\" }}\n    {%- endif %}\n{%- endfor %}\n{{- \" </tools>\" }}\n{{- 'Use the following pydantic model json schema for each tool call you will make: {\"properties\": {\"name\": {\"title\": \"Name\", \"type\": \"string\"}, \"arguments\": {\"title\": \"Arguments\", \"type\": \"object\"}}, \"required\": [\"name\", \"arguments\"], \"title\": \"FunctionCall\", \"type\": \"object\"}}\n' }}\n{{- \"For each function call return a json object with function name and arguments within <tool_call></tool_call> XML tags as follows:\n\" }}\n{{- \"<tool_call>\n\" }}\n{{- '{\"name\": <function-name>, \"arguments\": <args-dict>}\n' }}\n{{- '</tool_call><|im_end|>' }}\n{%- for message in messages %}\n    {%- if message.role == \"user\" or message.role == \"system\" or (message.role == \"assistant\" and message.tool_calls is not defined) %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role }}\n    {%- for tool_call in message.tool_calls %}\n       {{- '\n<tool_call>\n' }}           {%- if tool_call.function is defined %}\n                {%- set tool_call = tool_call.function %}\n            {%- endif %}\n            {{- '{' }}\n            {{- '\"name\": \"' }}\n            {{- tool_call.name }}\n            {{- '\"}' }}\n            {{- ', '}}\n            {%- if tool_call.arguments is defined %}\n                {{- '\"arguments\": ' }}\n                {{- tool_call.arguments|tojson }}\n            {%- endif %}\n            {{- '\\n</tool_call>' }}\n    {%- endfor %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if not message.name is defined %}\n            {{- raise_exception(\"Tool response dicts require a 'name' key indicating the name of the called function!\") }}\n        {%- endif %}\n        {%- if loop.previtem and loop.previtem.role != \"tool\" %}\n            {{- '<|im_start|>tool\\n' }}\n        {%- endif %}\n        {{- '<tool_response>\\n' }}\n        {{- message.content }}\n        {%- if not loop.last %}\n            {{- '\\n</tool_response>\\n' }}\n        {%- else %}\n            {{- '\\n</tool_response>' }}\n        {%- endif %}\n        {%- if not loop.last and loop.nextitem.role != \"tool\" %}\n            {{- '<|im_end|>' }}\n        {%- elif loop.last %}\n            {{- '<|im_end|>' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n"
+    }
+  ],
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|im_end|>",
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 131072,
+  "pad_token": "<|end_of_text|>",
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}