marrywise-llm: A Python repository from sáofund

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marrywise_ops.mp4

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).

Input (Conditions)	Output (After analysis, large model conversion)
1. 32 years old, 178cm 2. Collects rent, annual income of 15104 3. 6 houses, one car 4. Loves cleanliness, cooking, wife, parents divorced and lives with mother, mother is gentle.	🔍 Hidden Secrets: The truth he doesn't want you to know In the dazzling matchmaking market, everyone tries to show their best side. But beware of those unspoken secrets, they could be stumbling blocks on your path to happiness. 🍳 The weight mystery behind cooking He claims to be a cooking master, living an easy and comfortable life. But numbers don't lie: the undisclosed weight may hint at an unhealthy lifestyle. Don't overlook long-term health risks while enjoying the delicacies. 💰 Questions about property origin Six properties, one car—seemingly solid financial foundation. But where do these assets come from? Being a demolition household might signify luck, or it could indicate a lack of ambition. 👨‍👩‍👦 Complexity of family relationships He praises his mother's gentleness and easy-going nature, but does it mean he cannot be independent? The mother-son relationship in a single-parent family may be more complex than it appears, potentially affecting future family harmony. 💍 The "loving wife" label trap "Loving wife" sounds perfect, but beware it could be a psychological tactic. Don't be easily fooled by this label without delving into his true intentions. 🔍 Deep Dive: What are the real motives? He understands women, but why is he still single? There might be hidden secrets under his perfect exterior. Uncover the veil and see his true motives before making a decision.

Input (Conditions)

Output (After analysis, large model conversion)

1. 32 years old, 178cm
2. Collects rent, annual income of 15104
3. 6 houses, one car
4. Loves cleanliness, cooking, wife, parents divorced and lives with mother, mother is gentle.

🔍 Hidden Secrets: The truth he doesn't want you to know
In the dazzling matchmaking market, everyone tries to show their best side. But beware of those unspoken secrets, they could be stumbling blocks on your path to happiness.
🍳 The weight mystery behind cooking
He claims to be a cooking master, living an easy and comfortable life. But numbers don't lie: the undisclosed weight may hint at an unhealthy lifestyle. Don't overlook long-term health risks while enjoying the delicacies.
💰 Questions about property origin
Six properties, one car—seemingly solid financial foundation. But where do these assets come from? Being a demolition household might signify luck, or it could indicate a lack of ambition.
👨‍👩‍👦 Complexity of family relationships
He praises his mother's gentleness and easy-going nature, but does it mean he cannot be independent? The mother-son relationship in a single-parent family may be more complex than it appears, potentially affecting future family harmony.
💍 The "loving wife" label trap
"Loving wife" sounds perfect, but beware it could be a psychological tactic. Don't be easily fooled by this label without delving into his true intentions.
🔍 Deep Dive: What are the real motives?
He understands women, but why is he still single? There might be hidden secrets under his perfect exterior. Uncover the veil and see his true motives before making a decision.

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
git clone https://huggingface.co/saofund/marrywise-7b-lora

# 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:

Contact the Author

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

Author's WeChat QR Code	sáo Fund Sponsorship

For dataset acquisition, models, algorithms, technical exchanges, and collaborative development, feel free to add the author's WeChat.	Sponsored by sáo Fund, thank you.