MonadGPT
| Property | Value |
|---|---|
| Parameter Count | 7.24B |
| Model Type | Text Generation (Conversational) |
| Architecture | Mistral-based (OpenHermes-2) |
| License | Apache-2.0 |
| Supported Languages | English, French, Latin |
| Tensor Type | BF16 |
What is MonadGPT?
MonadGPT is a fascinating experiment that reimagines what AI language models might have looked like if they were created in the 17th century. Built on the OpenHermes-2-Mistral-7B architecture, this model has been fine-tuned on 11,000 early modern texts from EEBO and Gallica, creating a unique conversational experience that mimics historical language patterns and knowledge frameworks.
Implementation Details
The model utilizes the ChatML format and requires a specific system prompt to maintain its historical persona. It's implemented using the Transformers library and can be run using either Hugging Face Transformers or llama.cpp for optimized performance. A quantized GGUF version is available for improved efficiency.
- Base Model: teknium/OpenHermes-2-Mistral-7B
- Training Data: 11,000 early modern texts
- Format: ChatML with specialized system prompts
- Deployment Options: Native or Quantized (GGUF)
Core Capabilities
- Historical Language Generation: Produces responses in archaic English, French, and Latin
- Period-Appropriate Knowledge: Provides answers based on 17th-century understanding of science and philosophy
- Multi-lingual Support: Functions in three historical languages
- Conversational Interface: Maintains period-appropriate dialogue patterns
Frequently Asked Questions
Q: What makes this model unique?
MonadGPT stands out for its authentic recreation of 17th-century knowledge and communication styles, making it valuable for historical research, educational purposes, and creative projects requiring period-appropriate dialogue.
Q: What are the recommended use cases?
The model is best suited for historical simulations, educational demonstrations, creative writing in historical contexts, and exploring how historical figures might have approached modern questions. However, it's important to note that the model's medical and scientific advice should not be followed as it reflects outdated understanding.
