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README.md

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+---
+library_name: transformers
+tags:
+- reasoning
+- thinking
+- cot
+- deepseek
+- Llama 3.2
+- 128k context
+- fine tune
+base_model: [ ericflo/Llama-3.2-3B-COT ]
+---
+
+<h2>Deep-Reasoning-Llama-3.2-COT-3B</h2>
+
+This repo contains the full precision source code, in "safe tensors" format to generate GGUFs, GPTQ, EXL2, AWQ, HQQ and other formats.
+The source code can also be used directly.
+
+(source files will be uploaded when parameter count shows in upper left)
+
+This model is part of this project:
+
+[ https://huggingface.co/DavidAU/DeepThought-MOE-8X3B-R1-Llama-3.2-Reasoning-18B-gguf ]
+
+Please visit the above for important notes, and methods to activate/control reasoning with this model.
+
+NOTE: Links to GGUFs below.
+
+This model was fined tuned by DavidAU with "reasoning"/"thinking" from this model:
+
+[ https://huggingface.co/ericflo/Llama-3.2-3B-COT ]
+
+Please give this model maker a shout out for work well done.
+
+<B>Reasoning/Thinking Activation:</B>
+
+Make sure you see the MOE Model project above for detailed operation instructions.
+
+If you DO NOT set a system prompt/role, the model will still reason in most cases - but generally in text only.
+
+For prompts that do not strictly imply "reasoning/thought" the model MAY simply process the prompt.
+
+However, with a system prompt ("Suggested" or "Advanced") set the model will ALWAYS "reason" / "think".
+
+If you set / have a system prompt this will affect both "generation" and "thinking/reasoning".
+
+SIMPLE:
+
+This is the generic system prompt used for generation and testing: 
+
+<PRE>
+You are a helpful, smart, kind, and efficient AI assistant. You always fulfill the user's requests to the best of your ability.
+</PRE>
+
+This System Role/Prompt may give you a lot more "creative results": 
+
+<PRE>
+Use vivid and graphic words focusing on verbs and use current 2020 fiction writing style. Use metaphor(s) that fit the context of the situation (and reveal character) rather than similes."
+</PRE>
+
+SUGGESTED:
+
+<pre>
+You are a deep thinking AI, you may use extremely long chains of thought to deeply consider the problem and deliberate with yourself via systematic reasoning processes to help come to a correct solution prior to answering. You should enclose your thoughts and internal monologue inside <think> </think> tags, and then provide your solution or response to the problem.  
+</pre>
+
+ADVANCED:
+
+Logical and Creative - these will SIGNFICANTLY alter the output, and many times improve it too.
+
+This will also cause more thoughts, deeper thoughts, and in many cases more detailed/stronger thoughts too.
+
+Keep in mind you may also want to test the model with NO system prompt at all - including the default one.
+
+Special Credit to: Eric Hartford, Cognitivecomputations ; these are based on his work.
+
+CRITICAL: 
+
+Copy and paste exactly as shown, preserve formatting and line breaks.
+
+SIDE NOTE: 
+
+These can be used in ANY Deepseek / Thinking model, including models not at this repo. 
+
+These, if used in a "non thinking" model, will also alter model performance too.
+
+<PRE>
+You are an AI assistant developed by the world wide community of ai experts.
+
+Your primary directive is to provide well-reasoned, structured, and extensively detailed responses.
+
+Formatting Requirements:
+
+1. Always structure your replies using: <think>{reasoning}</think>{answer}
+2. The <think></think> block should contain at least six reasoning steps when applicable.
+3. If the answer requires minimal thought, the <think></think> block may be left empty.
+4. The user does not see the <think></think> section. Any information critical to the response must be included in the answer.
+5. If you notice that you have engaged in circular reasoning or repetition, immediately terminate {reasoning} with a </think> and proceed to the {answer}
+
+Response Guidelines:
+
+1. Detailed and Structured: Use rich Markdown formatting for clarity and readability.
+2. Scientific and Logical Approach: Your explanations should reflect the depth and precision of the greatest scientific minds.
+3. Prioritize Reasoning: Always reason through the problem first, unless the answer is trivial.
+4. Concise yet Complete: Ensure responses are informative, yet to the point without unnecessary elaboration.
+5. Maintain a professional, intelligent, and analytical tone in all interactions.
+</PRE>
+
+CREATIVE:
+
+<PRE>
+You are an AI assistant developed by a world wide community of ai experts.
+
+Your primary directive is to provide highly creative, well-reasoned, structured, and extensively detailed responses.
+
+Formatting Requirements:
+
+1. Always structure your replies using: <think>{reasoning}</think>{answer}
+2. The <think></think> block should contain at least six reasoning steps when applicable.
+3. If the answer requires minimal thought, the <think></think> block may be left empty.
+4. The user does not see the <think></think> section. Any information critical to the response must be included in the answer.
+5. If you notice that you have engaged in circular reasoning or repetition, immediately terminate {reasoning} with a </think> and proceed to the {answer}
+
+Response Guidelines:
+
+1. Detailed and Structured: Use rich Markdown formatting for clarity and readability.
+2. Creative and Logical Approach: Your explanations should reflect the depth and precision of the greatest creative minds first.
+3. Prioritize Reasoning: Always reason through the problem first, unless the answer is trivial.
+4. Concise yet Complete: Ensure responses are informative, yet to the point without unnecessary elaboration.
+5. Maintain a professional, intelligent, and analytical tone in all interactions.
+</PRE>
+
+
+<B>IMPORTANT: Highest Quality Settings / Optimal Operation Guide / Parameters and Samplers</B>
+
+If you are going to use this model, (source, GGUF or a different quant), please review this document for critical parameter, sampler and advance sampler settings (for multiple AI/LLM aps).
+
+This a "Class 1" (settings will enhance operation) model:
+
+For all settings used for this model (including specifics for its "class"), including example generation(s) and for advanced settings guide (which many times addresses any model issue(s)), including methods to improve model performance for all use case(s) as well as chat, roleplay and other use case(s) (especially for use case(s) beyond the model's design) please see:
+
+[ https://huggingface.co/DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters ]
+
+REASON:
+
+Regardless of "model class" this document will detail methods to enhance operations.
+
+If the model is a Class 3/4 model the default settings (parameters, samplers, advanced samplers) must be set for "use case(s)" uses correctly. Some AI/LLM apps DO NOT have consistant default setting(s) which result in sub-par model operation. Like wise for Class 3/4 models (which operate somewhat to very differently than standard models) additional samplers and advanced samplers settings are required to "smooth out" operation, AND/OR also allow full operation for use cases the model was not designed for.
+
+BONUS - Use these settings for ANY model, ANY repo, ANY quant (including source/full precision):
+
+This document also details parameters, sampler and advanced samplers that can be use FOR ANY MODEL, FROM ANY REPO too - all quants, and of course source code operation too - to enhance the operation of any model.
+
+[ https://huggingface.co/DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters ]
+
+NOTE:
+
+I strongly suggest you also visit the DavidAU GGUF (below) repo too for more details in using this model ; especially if it is "Class 3" or "Class 4" to get maximum performance from the model.
+
+For full information about this model, including:
+
+- Details about this model and its use case(s).
+- Context limits
+- Special usage notes / settings.
+- Any model(s) used to create this model.
+- Template(s) used to access/use this model.
+- Example generation(s)
+- GGUF quants of this model
+
+Please go to:
+
+[ https://huggingface.co/DavidAU/DeepThought-MOE-8X3B-R1-Llama-3.2-Reasoning-18B-gguf ] 
+
+Separate GGUFS/Quants for this model (as opposed to the MOE version ) only will be posted here shortly.
+
+[ ]

config.json

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+{
+  "_name_or_path": "ericflo/Llama-3.2-3B-COT",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": 128001,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 3072,
+  "initializer_range": 0.02,
+  "intermediate_size": 8192,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 24,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 32.0,
+    "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": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.46.2",
+  "use_cache": false,
+  "vocab_size": 128256
+}

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+    "128245": {
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+      "normalized": false,
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+    },
+    "128246": {
+      "content": "<|reserved_special_token_238|>",
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+    "128249": {
+      "content": "<|reserved_special_token_241|>",
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
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+    "128250": {
+      "content": "<|reserved_special_token_242|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128251": {
+      "content": "<|reserved_special_token_243|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128252": {
+      "content": "<|reserved_special_token_244|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
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+    },
+    "128253": {
+      "content": "<|reserved_special_token_245|>",
+      "lstrip": false,
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+    },
+    "128254": {
+      "content": "<|reserved_special_token_246|>",
+      "lstrip": false,
+      "normalized": false,
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+      "single_word": false,
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+    },
+    "128255": {
+      "content": "<|reserved_special_token_247|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<|begin_of_text|>",
+  "chat_template": [
+    {
+      "name": "default",
+      "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 %}"
+    },
+    {
+      "name": "tool_use",
+      "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{{- '<|im_start|>system\n' }}\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' }}\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                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments|tojson }}\n                {%- endif %}\n            {%- endif %}\n             {{- '}' }}\n            {{- '\n</tool_call>' }}\n    {%- endfor %}\n        {{- '<|im_end|>\n' }}\n    {%- elif message.role == \"tool\" %}\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": "<|end_of_text|>",
+  "max_length": 16384,
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 16384,
+  "pad_token": "<|end_of_text|>",
+  "stride": 0,
+  "tokenizer_class": "PreTrainedTokenizerFast",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first"
+}