marrywise-7b-lora

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[ English | 中文 ]

<!-- **MarryWise: AI-Driven Matchmaking Analysis Tool** -->

Features

• AI Matchmaking Analyst: Utilizing advanced AI technology to automatically analyze behavior and speech patterns during dates, revealing hidden motives and true personality traits.
• AI Fake Matchmaker Detector: Helps users identify potential deceitful behavior during the dating process, ensuring the authenticity and reliability of partners.

Main Analysis Dimensions

• Personality Authenticity: Assessing the true character of a potential partner through behavior and speech analysis.
• Actual Motives: Revealing the real intentions behind a suitor's actions to prevent being deceived by appearances.
• Personal Achievements: Evaluating a suitor's personal achievements and capabilities to ensure their descriptions match reality.

Fine-tuning Data Example

Fine-tuned using Qwen2-7B, example of fine-tuning data (coming soon).

Local Setup

Detailed Steps:

# Download Qwen2-7B-Instruct model: https://modelscope.cn/models/qwen/Qwen2-7B/files
git lfs install
git clone https://www.modelscope.cn/qwen/Qwen2-7B.git

# Download lora weights

# Install LLaMA-Factory
git clone --depth 1 https://github.com/hiyouga/LLaMA-Factory.git    
cd LLaMA-Factory
pip install -e ".[torch,metrics]"   # Install dependencies, follow the official instructions

# Use LLaMA-Factory to merge lora weights
# Requires GPU, approximately 12G VRAM usage
llamafactory-cli export \
        --model_name_or_path Qwen2-7B-Instruct \    # The just downloaded Qwen2-7B weights
        --adapter_name_or_path output_qwen\         # Path to lora weights
        --template qwen \                           # Default
        --finetuning_type lora \                    # Default
        --export_dir lora_full_param_model \        # Output path for full weights
        --export_size 2 \                           # Default
        --export_legacy_format False                # Default

# Official Qwen2 inference test script, replace the weight path with the merged path
python cli_demo.py -c path_to_merged_weights  # Approximately 15G VRAM

# Note: Due to the "style" characteristics of lora fine-tuning, specific prompt words need to be added at the beginning of the question:
# Your role is a matchmaking condition analyst, specializing in identifying the "hidden" conditions not mentioned by the male party, analyzing the "secrets not mentioned" in matchmaking. xxxx (followed by specific conditions)

Local CLI Result:

<img src="assets/sft_demo.png" width="500" alt="CLI Result">

Contact the Author

For dataset acquisition, models, algorithms, technical exchanges, and collaborative development, feel free to add the author's WeChat.