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MonadGPT GPTQ by TheBloke

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MonadGPT GPTQ is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 4.2GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.1.

  4-bit   Base model:pclanglais/monadgpt Base model:quantized:pclanglai...   Conversational   En   Fr   Gptq   La   Mistral   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/TheBloke/MonadGPT-GPTQ 

MonadGPT GPTQ Benchmarks

LLME Score: 0.10423
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MonadGPT GPTQ (TheBloke/MonadGPT-GPTQ)
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MonadGPT GPTQ Parameters and Internals

Model Type 
mistral
Use Cases 
Areas:
research, educational
Primary Use Cases:
Generating text in a 17th-century style, Answering questions with historical context
Limitations:
Conversational accuracy, Localization issues
Considerations:
Not suitable for modern or technical questions
Additional Notes 
MonadGPT is trained on early modern texts and answers in an archaic style, often leading to inaccuracies in modern contexts.
Supported Languages 
en (proficient), fr (proficient), la (basic)
Input Output 
Input Format:
ChatML format with special system prompt
Accepted Modalities:
text
LLM NameMonadGPT GPTQ
Repository 🤗https://huggingface.co/TheBloke/MonadGPT-GPTQ 
Model NameMonadGPT 7B
Model CreatorPierre-Carl Langlais
Base Model(s)  MonadGPT   Pclanglais/MonadGPT
Model Size7b
Required VRAM4.2 GB
Updated2025-12-10
MaintainerTheBloke
Model Typemistral
Model Files  4.2 GB
Supported Languagesen fr la
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.34.1
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32002
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/MonadGPT-GPTQ.

Rank the MonadGPT GPTQ Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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