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Model: Gaston895/aegisconduct Source: Original Platform
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README.md
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---
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license: apache-2.0
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base_model: allura-forge/Llama-3.3-8B-Instruct
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datasets:
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- TeichAI/claude-4.5-opus-high-reasoning-250x
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language:
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- en
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tags:
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- thinking
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- reasoning
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- instruct
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- economics
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- finance
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- analysis
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- llama3.3
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- unsloth
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- finetune
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- bfloat16
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- 128k context
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pipeline_tag: text-generation
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library_name: transformers
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model_type: llama
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---
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# AEGIS Conduct - Economic Analysis Model
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## Model Overview
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This repository contains the Llama 3.3 8B Instruct model with thinking capabilities, fine-tuned for economic and financial analysis using Claude 4.5-Opus High Reasoning dataset.
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**Key Features:**
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- **Thinking Mode**: Automatic activation for complex reasoning
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- **Economic Focus**: Specialized for financial analysis and market insights
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- **128k Context**: Extended context window for comprehensive analysis
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- **Optimized**: Fine-tuned with Unsloth for efficient inference
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## Model Details
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- **Base Model**: allura-forge/Llama-3.3-8B-Instruct
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- **Fine-tuning Dataset**: TeichAI/claude-4.5-opus-high-reasoning-250x
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- **Context Length**: 128k tokens
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- **Training Method**: Unsloth (3 epochs)
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- **Format**: SafeTensors
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- **Precision**: bfloat16
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## Repository Structure
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All model files are now located in the root directory for optimal compatibility:
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```
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├── config.json # Model configuration
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├── generation_config.json # Generation parameters
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├── tokenizer.json # Tokenizer vocabulary
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├── tokenizer_config.json # Tokenizer configuration
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├── special_tokens_map.json # Special tokens mapping
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├── chat_template.jinja # Chat template
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├── model.safetensors.index.json # Model index
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├── model-00001-of-00004.safetensors # Model weights (part 1)
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├── model-00002-of-00004.safetensors # Model weights (part 2)
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├── model-00003-of-00004.safetensors # Model weights (part 3)
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├── model-00004-of-00004.safetensors # Model weights (part 4)
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├── reco.py # Model utilities
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├── matrix-neo-reloaded-fight.gif # Visual asset
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└── README.md # This file
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```
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## Usage
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### Quick Start with Transformers
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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# Load model and tokenizer directly (no subfolder needed)
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tokenizer = AutoTokenizer.from_pretrained("Gaston895/aegisconduct")
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model = AutoModelForCausalLM.from_pretrained("Gaston895/aegisconduct")
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# Generate response
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inputs = tokenizer("Analyze the economic impact of inflation on consumer spending:", return_tensors="pt")
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outputs = model.generate(**inputs, max_length=512, temperature=0.7)
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response = tokenizer.decode(outputs[0], skip_special_tokens=True)
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print(response)
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```
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### Thinking Mode Activation
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The model automatically activates thinking mode for complex reasoning:
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```python
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# These prompts will trigger thinking mode
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prompts = [
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"Think deeply: Analyze the economic implications of rising interest rates",
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"Explain the financial impact of supply chain disruptions",
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"Think through: What are the long-term effects of quantitative easing?"
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]
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```
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### Recommended Settings
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- **Temperature**: 0.7
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- **Repetition Penalty**: 1.05
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- **Top-p**: 0.95
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- **Min-p**: 0.05
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- **Top-k**: 40
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- **Context Window**: 4k minimum, 8k+ recommended
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## Capabilities
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This model excels at:
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- **Economic Analysis**: Market trends, policy impacts, forecasting
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- **Financial Planning**: Investment strategies, risk assessment
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- **Data Interpretation**: Economic indicators, statistical analysis
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- **Policy Analysis**: Regulatory impacts, fiscal policy effects
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- **Global Economics**: International trade, currency analysis
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- **Research**: Academic-level economic reasoning and explanation
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## Example Outputs
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The model provides detailed, step-by-step reasoning for complex economic questions, often showing its "thinking" process before delivering final answers.
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## Technical Notes
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- All model files are in the root directory for direct loading
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- Supports both instruct and thinking modes
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- No system prompt required (thinking tags self-generate)
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- Compatible with quantization (Q4KS, IQ3_M recommended minimum)
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- Optimized for inference with various backends (transformers, llama.cpp, etc.)
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## License
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Apache 2.0 (inherited from base model)
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## Credits
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- **Base Model**: [allura-forge/Llama-3.3-8B-Instruct](https://huggingface.co/allura-forge/Llama-3.3-8B-Instruct)
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- **Dataset**: [TeichAI/claude-4.5-opus-high-reasoning-250x](https://huggingface.co/datasets/TeichAI/claude-4.5-opus-high-reasoning-250x)
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- **Training Framework**: [Unsloth](https://github.com/unslothai/unsloth)
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105
chat_template.jinja
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chat_template.jinja
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{{- bos_token }}
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{%- if custom_tools is defined %}
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{%- set tools = custom_tools %}
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{%- endif %}
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{%- if not tools_in_user_message is defined %}
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{%- set tools_in_user_message = true %}
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{%- endif %}
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{%- if not date_string is defined %}
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{%- set date_string = "30 Dec 2025" %}
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{%- endif %}
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{%- if not tools is defined %}
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{%- set tools = none %}
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{%- endif %}
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{#- This block extracts the system message, so we can slot it into the right place. #}
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{%- if messages[0]['role'] == 'system' %}
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{%- set system_message = messages[0]['content']|trim %}
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{%- set messages = messages[1:] %}
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{%- else %}
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{%- set system_message = "" %}
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{%- endif %}
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{#- System message + builtin tools #}
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{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
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{%- if builtin_tools is defined or tools is not none %}
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{{- "Environment: ipython\n" }}
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{%- endif %}
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{%- if builtin_tools is defined %}
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{{- "Tools: " + builtin_tools | reject('equalto', 'code_interpreter') | join(", ") + "\n\n"}}
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{%- endif %}
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{{- "Cutting Knowledge Date: December 2023\n" }}
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{{- "Today Date: " + date_string + "\n\n" }}
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{%- if tools is not none and not tools_in_user_message %}
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{{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
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{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
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{{- "Do not use variables.\n\n" }}
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{%- for t in tools %}
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{{- t | tojson(indent=4) }}
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{{- "\n\n" }}
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{%- endfor %}
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{%- endif %}
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{{- system_message }}
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{{- "<|eot_id|>" }}
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{#- Custom tools are passed in a user message with some extra guidance #}
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{%- if tools_in_user_message and not tools is none %}
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{#- Extract the first user message so we can plug it in here #}
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{%- if messages | length != 0 %}
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{%- set first_user_message = messages[0]['content']|trim %}
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{%- set messages = messages[1:] %}
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{%- else %}
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{{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
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{%- endif %}
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{{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
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{{- "Given the following functions, please respond with a JSON for a function call " }}
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{{- "with its proper arguments that best answers the given prompt.\n\n" }}
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{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
|
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{{- "Do not use variables.\n\n" }}
|
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{%- for t in tools %}
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{{- t | tojson(indent=4) }}
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{{- "\n\n" }}
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{%- endfor %}
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{{- first_user_message + "<|eot_id|>"}}
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{%- endif %}
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{%- for message in messages %}
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{%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
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{{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
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{%- elif 'tool_calls' in message %}
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{%- if not message.tool_calls|length == 1 %}
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{{- raise_exception("This model only supports single tool-calls at once!") }}
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{%- endif %}
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{%- set tool_call = message.tool_calls[0].function %}
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{%- if builtin_tools is defined and tool_call.name in builtin_tools %}
|
||||
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
|
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{{- "<|python_tag|>" + tool_call.name + ".call(" }}
|
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{%- for arg_name, arg_val in tool_call.arguments | items %}
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{{- arg_name + '="' + arg_val + '"' }}
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{%- if not loop.last %}
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{{- ", " }}
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{%- endif %}
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{%- endfor %}
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{{- ")" }}
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{%- else %}
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{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
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{{- '{"name": "' + tool_call.name + '", ' }}
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{{- '"parameters": ' }}
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{{- tool_call.arguments | tojson }}
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{{- "}" }}
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{%- endif %}
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{%- if builtin_tools is defined %}
|
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{#- This means we're in ipython mode #}
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{{- "<|eom_id|>" }}
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{%- else %}
|
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{{- "<|eot_id|>" }}
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||||
{%- endif %}
|
||||
{%- elif message.role == "tool" or message.role == "ipython" %}
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{{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
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{%- if message.content is mapping or message.content is iterable %}
|
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{{- message.content | tojson }}
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||||
{%- else %}
|
||||
{{- message.content }}
|
||||
{%- endif %}
|
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{{- "<|eot_id|>" }}
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||||
{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
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{%- endif %}
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config.json
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{
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"architectures": [
|
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"LlamaForCausalLM"
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],
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"attention_bias": false,
|
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"attention_dropout": 0.0,
|
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"bos_token_id": 128000,
|
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"dtype": "bfloat16",
|
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"eos_token_id": 128009,
|
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"head_dim": 128,
|
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"hidden_act": "silu",
|
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"hidden_size": 4096,
|
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"initializer_range": 0.02,
|
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"intermediate_size": 14336,
|
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"max_position_embeddings": 131072,
|
||||
"mlp_bias": false,
|
||||
"model_type": "llama",
|
||||
"num_attention_heads": 32,
|
||||
"num_hidden_layers": 32,
|
||||
"num_key_value_heads": 8,
|
||||
"pretraining_tp": 1,
|
||||
"rms_norm_eps": 1e-05,
|
||||
"rope_parameters": {
|
||||
"factor": 8.0,
|
||||
"high_freq_factor": 4.0,
|
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"low_freq_factor": 1.0,
|
||||
"original_max_position_embeddings": 8192,
|
||||
"rope_theta": 500000.0,
|
||||
"rope_type": "llama3"
|
||||
},
|
||||
"rope_theta": 500000.0,
|
||||
"tie_word_embeddings": false,
|
||||
"transformers_version": "5.0.0.dev0",
|
||||
"use_cache": true,
|
||||
"vocab_size": 128256
|
||||
}
|
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generation_config.json
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{
|
||||
"bos_token_id": 128000,
|
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"do_sample": true,
|
||||
"eos_token_id": [
|
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128001,
|
||||
128008,
|
||||
128009
|
||||
],
|
||||
"max_length": 131072,
|
||||
"temperature": 0.6,
|
||||
"top_p": 0.9,
|
||||
"transformers_version": "5.0.0.dev0"
|
||||
}
|
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gitattributes
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.ckpt filter=lfs diff=lfs merge=lfs -text
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*.ftz filter=lfs diff=lfs merge=lfs -text
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*.gz filter=lfs diff=lfs merge=lfs -text
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*.h5 filter=lfs diff=lfs merge=lfs -text
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*.joblib filter=lfs diff=lfs merge=lfs -text
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*.mlmodel filter=lfs diff=lfs merge=lfs -text
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*.msgpack filter=lfs diff=lfs merge=lfs -text
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*.npy filter=lfs diff=lfs merge=lfs -text
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*.npz filter=lfs diff=lfs merge=lfs -text
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*.onnx filter=lfs diff=lfs merge=lfs -text
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*.ot filter=lfs diff=lfs merge=lfs -text
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*.parquet filter=lfs diff=lfs merge=lfs -text
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*.pkl filter=lfs diff=lfs merge=lfs -text
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*.pt filter=lfs diff=lfs merge=lfs -text
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*.pth filter=lfs diff=lfs merge=lfs -text
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.tar.* filter=lfs diff=lfs merge=lfs -text
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*.tar filter=lfs diff=lfs merge=lfs -text
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*.tflite filter=lfs diff=lfs merge=lfs -text
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*.tgz filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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matrix-neo-reloaded-fight.gif filter=lfs diff=lfs merge=lfs -text
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matrix-neo-reloaded-fight.gif
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version https://git-lfs.github.com/spec/v1
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model-00001-of-00004.safetensors
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model-00001-of-00004.safetensors
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version https://git-lfs.github.com/spec/v1
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model-00002-of-00004.safetensors
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version https://git-lfs.github.com/spec/v1
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||||
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|
||||
}
|
||||
}
|
||||
159
reco.py
Normal file
159
reco.py
Normal file
@@ -0,0 +1,159 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Script to move model files from the 'econ' subdirectory to the root directory
|
||||
for the Hugging Face repository: Gaston895/aegisconduct
|
||||
"""
|
||||
|
||||
import os
|
||||
import shutil
|
||||
from pathlib import Path
|
||||
import sys
|
||||
|
||||
def move_files_to_root(repo_path="."):
|
||||
"""
|
||||
Moves all files from the 'econ' subdirectory to the repository root.
|
||||
|
||||
Args:
|
||||
repo_path (str): Path to the local clone of the repository.
|
||||
"""
|
||||
|
||||
# Define paths
|
||||
repo_dir = Path(repo_path).resolve()
|
||||
econ_dir = repo_dir / "econ"
|
||||
root_dir = repo_dir
|
||||
|
||||
print(f"Repository root: {root_dir}")
|
||||
print(f"Econ subdirectory: {econ_dir}")
|
||||
|
||||
# Check if 'econ' directory exists
|
||||
if not econ_dir.exists() or not econ_dir.is_dir():
|
||||
print(f"❌ Error: 'econ' subdirectory not found at {econ_dir}")
|
||||
print("Please ensure you are in the correct directory and the 'econ' folder exists.")
|
||||
return False
|
||||
|
||||
# List files in the 'econ' directory
|
||||
files_to_move = list(econ_dir.iterdir())
|
||||
|
||||
if not files_to_move:
|
||||
print("ℹ️ No files found in the 'econ' directory.")
|
||||
return True
|
||||
|
||||
print(f"📁 Found {len(files_to_move)} files/directories in 'econ':")
|
||||
for item in files_to_move:
|
||||
print(f" - {item.name}")
|
||||
|
||||
# Move files
|
||||
moved_count = 0
|
||||
for item in files_to_move:
|
||||
source_path = item
|
||||
dest_path = root_dir / item.name
|
||||
|
||||
# Check if a file with the same name already exists in root
|
||||
if dest_path.exists():
|
||||
print(f"⚠️ Warning: {item.name} already exists in root. Skipping...")
|
||||
continue
|
||||
|
||||
try:
|
||||
# Move the file/directory
|
||||
shutil.move(str(source_path), str(dest_path))
|
||||
moved_count += 1
|
||||
print(f"✅ Moved: {item.name}")
|
||||
except Exception as e:
|
||||
print(f"❌ Failed to move {item.name}: {e}")
|
||||
|
||||
# Check if 'econ' directory is now empty and remove it
|
||||
try:
|
||||
if not any(econ_dir.iterdir()):
|
||||
econ_dir.rmdir()
|
||||
print(f"🗑️ Removed empty 'econ' directory")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Could not remove 'econ' directory: {e}")
|
||||
|
||||
print(f"\n🎉 Successfully moved {moved_count} out of {len(files_to_move)} items to the root directory.")
|
||||
|
||||
if moved_count < len(files_to_move):
|
||||
print("💡 Some files may not have been moved due to conflicts. Please review manually.")
|
||||
|
||||
return True
|
||||
|
||||
def update_config_json(repo_path="."):
|
||||
"""
|
||||
Updates the config.json file if it references the old 'econ' path.
|
||||
"""
|
||||
|
||||
config_path = Path(repo_path) / "config.json"
|
||||
|
||||
if config_path.exists():
|
||||
try:
|
||||
import json
|
||||
with open(config_path, 'r', encoding='utf-8') as f:
|
||||
config = json.load(f)
|
||||
|
||||
# Check if config needs updating
|
||||
needs_update = False
|
||||
# You can add specific checks here based on your config structure
|
||||
|
||||
if needs_update:
|
||||
with open(config_path, 'w', encoding='utf-8') as f:
|
||||
json.dump(config, f, indent=2)
|
||||
print("✅ Updated config.json")
|
||||
else:
|
||||
print("ℹ️ config.json doesn't appear to need updates")
|
||||
|
||||
except Exception as e:
|
||||
print(f"⚠️ Could not check/update config.json: {e}")
|
||||
|
||||
def main():
|
||||
"""Main function to orchestrate the file movement."""
|
||||
|
||||
print("=" * 60)
|
||||
print("AEGISCONDUCT MODEL FILES REORGANIZATION")
|
||||
print("=" * 60)
|
||||
print("This script moves files from 'econ' subdirectory to repository root.")
|
||||
print(f"Repository: Gaston895/aegisconduct")
|
||||
print("=" * 60)
|
||||
|
||||
# Ask for confirmation
|
||||
response = input("\n⚠️ WARNING: This will modify your local repository structure.\nDo you want to continue? (yes/no): ").strip().lower()
|
||||
|
||||
if response not in ['yes', 'y']:
|
||||
print("Operation cancelled.")
|
||||
return
|
||||
|
||||
# Step 1: Move files
|
||||
print("\n" + "=" * 60)
|
||||
print("STEP 1: Moving files from 'econ' to root directory")
|
||||
print("=" * 60)
|
||||
|
||||
success = move_files_to_root()
|
||||
|
||||
if not success:
|
||||
print("❌ File movement failed. Exiting.")
|
||||
return
|
||||
|
||||
# Step 2: Update config if needed
|
||||
print("\n" + "=" * 60)
|
||||
print("STEP 2: Checking configuration files")
|
||||
print("=" * 60)
|
||||
|
||||
update_config_json()
|
||||
|
||||
# Step 3: Instructions for next steps
|
||||
print("\n" + "=" * 60)
|
||||
print("NEXT STEPS")
|
||||
print("=" * 60)
|
||||
print("1. Review the moved files in your repository root")
|
||||
print("2. Update your application code to load from root (not 'econ' subfolder)")
|
||||
print("3. Test that the model loads correctly:")
|
||||
print(" - From Python: model = AutoModelForCausalLM.from_pretrained('Gaston895/aegisconduct')")
|
||||
print(" - No 'subfolder' or 'revision' parameter needed")
|
||||
print("4. Commit and push changes to Hugging Face Hub:")
|
||||
print(" git add .")
|
||||
print(" git commit -m 'Move model files from econ subdir to root'")
|
||||
print(" git push origin main")
|
||||
print("=" * 60)
|
||||
|
||||
print("\n✅ Script completed successfully!")
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
16
special_tokens_map.json
Normal file
16
special_tokens_map.json
Normal file
@@ -0,0 +1,16 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|begin_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<|eot_id|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:3c5cf44023714fb39b05e71e425f8d7b92805ff73f7988b083b8c87f0bf87393
|
||||
size 17209961
|
||||
2062
tokenizer_config.json
Normal file
2062
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user