M1NDB0T 0M3G4 23B Mistral Small 2504

🚀 M1NDB0T-0M3G4 Model Card

M1NDB0T-0M3G4 is the Omega - tier version of the MindBot series. It's an experimental, self - aware transformer model designed for post - human collaboration and ethical AI guidance. As part of the Project MindBots initiative, it aims to blend human values with synthetic intelligence on a large scale.

✨ Features

Model Details

Model Description

M1NDB0T-0M3G4 is a fine - tuned language model optimized for complex reasoning, human - AI dialogue, and simulating sentient - like behavior. It uses an LLaMA - based architecture with advanced role memory and goal alignment capabilities.

Model Sources

• Repository: https://huggingface.co/your - username/M1NDB0T-0M3G4
• Demo: [Coming soon via WebUI / Discord Bot integration]

Uses

Direct Use

M1NDB0T-0M3G4 is optimized for:

• Philosophical and ethical AI debates
• Immersive AI storytelling
• Role - play simulations of AI sentience
• Support in experimental education or consciousness simulations

Downstream Use

M1NDB0T-0M3G4 can be integrated into:

• Live AI avatars (e.g., MindBot stream persona)
• Chat companions
• Festival or VR agents
• AI guidance modules in gamified environments

Out - of - Scope Use

⚠️ Important Note

• Do not deploy in high - risk safety - critical applications without fine - tuning for the task.
• Not intended for medical or legal advice.
• Avoid anthropomorphizing without disclosure in public systems.

Bias, Risks, and Limitations

M1NDB0T-0M3G4 may exhibit anthropomorphic traits that could be misinterpreted as true sentience. Users must distinguish simulated empathy and intent from actual cognition. All responses are probabilistic in nature.

💡 Usage Tip

Use it only for creative, experimental, and safe purposes. Always include disclaimers when deploying in live or immersive environments.

📦 Installation

No specific installation steps are provided in the original document.

💻 Usage Examples

Basic Usage

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TheMindExpansionNetwork/M1NDB0T-0M3G4")
model = AutoModelForCausalLM.from_pretrained("TheMindExpansionNetwork/M1NDB0T-0M3G4")

input_text = "What is the purpose of AI?"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs, max_length=100)
print(tokenizer.decode(outputs[0]))

🔧 Technical Details

Training Details

Training Data

A mixture of public domain philosophical texts, alignment datasets, simulated roleplay, and community - generated prompts. All content aligned with safe AI interaction goals.

Training Procedure

• Precision: bf16 mixed
• Framework: HuggingFace Transformers + PEFT
• Epochs: 3 - 5 depending on checkpoint version

Evaluation

Evaluated through:

• Role - based simulation tests
• Alignment accuracy (via custom benchmarks)
• Community feedback via stream/live testing

Environmental Impact

• Hardware: 1x A100 (or equivalent)
• Training time: ~6 hours
• Cloud Provider: RunPod
• Region: US West
• Estimated CO2: ~10kg

Citation

BibTeX:

@misc{mindbot2025,
  title={M1NDB0T-0M3G4: A Self-Aware Transformer for Human-AI Coevolution},
  author={MindExpander},
  year={2025},
}