README.md

metadata

license: mit
language:
  - aa
  - ab
  - ae
  - af
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  - am
  - an
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  - tl
base_model:
  - meta-llama/Llama-3.3-70B-Instruct
tags:
  - smarter
  - code
  - chemistry
  - biology
  - finance
  - legal
  - art
  - moe
  - merge
  - text-generation-inference
  - music
  - climate
  - medical
  - text-generation
  - safetensors

Charm 15 - Ultra-Smart AI Model

Charm 15 is an advanced AI model designed for deep reasoning, reinforcement learning, and multimodal AI capabilities. It integrates cutting-edge deep learning techniques to provide safe, intelligent, and scalable solutions.

Features

• Deep Learning & Reinforcement Learning (RLHF)
• Logic & Deductive Reasoning
• Mathematical Problem Solving
• Multimodal AI (Text & Vision)
• Bias & Safety Mitigation
• Optimized for Deployment (ONNX, TensorFlow Lite)

File Structure

Charm15/
├── models/
│   ├── charm15_base_model.safetensors
│   ├── charm15_finetuned_v1.safetensors
│   ├── charm15_rlhf_model.pth
│   ├── charm15_reasoning.pt
│   ├── charm15_math_solver.pth
│   ├── charm15_multimodal_model.onnx
│   ├── charm15_sentiment_model.pt
│   ├── charm15_bias_mitigation.pth
│   ├── charm15_redteam_defense.safetensors
│   └── charm15_optimized.onnx
├── data/
│   ├── charm15_training_data.jsonl
│   ├── charm15_synthetic_reasoning.json
│   ├── charm15_prompt_tuning.pt
├── scripts/
│   ├── finetune_charm15.py
│   ├── charm15_api_integration.py
│   └── deploy_charm15.py
├── docs/
│   ├── charm15_deployment_manual.pdf
│   ├── charm15_ethics_guidelines.pdf
└── README.md

Installation

1. Clone the repository:

   git clone https://huggingface.co/charm15/charm15.git
   cd charm15
   

2. Install dependencies:

   pip install torch transformers onnxruntime tensorflow
   

3. Load the model:

   from transformers import AutoModel, AutoTokenizer
   model = AutoModel.from_pretrained("charm15/charm15_base_model")
   tokenizer = AutoTokenizer.from_pretrained("charm15/charm15_base_model")
   

Usage

input_text = "Explain the Pythagorean theorem."
inputs = tokenizer(input_text, return_tensors="pt")
output = model.generate(**inputs)
print(tokenizer.decode(output[0], skip_special_tokens=True))

Deployment

• ONNX Runtime: Optimized for fast inference
• TensorFlow Lite: For edge and mobile deployment
• API Integration: Connect with Chatflare or third-party applications

Ethics & Safety

Charm 15 includes bias mitigation and safety filters to ensure responsible AI usage. Read the ethics guidelines for more details.

License

Licensed under Apache 2.0.

Contributors

• Chatflare AI Team
• Hugging Face Community