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MN GRAND Gutenberg Lyra4 Lyra 12B MADNESS by DavidAU

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MN GRAND Gutenberg Lyra4 Lyra 12B MADNESS is an open-source language model by DavidAU. Features: 12b LLM, VRAM: 23.8GB, Context: 1000K, LLM Explorer Score: 0.16.

  Conversational   Endpoints compatible   Merge   Mergekit   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/DavidAU/MN-GRAND-Gutenberg-Lyra4-Lyra-12B-MADNESS 

MN GRAND Gutenberg Lyra4 Lyra 12B MADNESS Benchmarks

LLME Score: 0.15566
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MN GRAND Gutenberg Lyra4 Lyra 12B MADNESS (DavidAU/MN-GRAND-Gutenberg-Lyra4-Lyra-12B-MADNESS)
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MN GRAND Gutenberg Lyra4 Lyra 12B MADNESS Parameters and Internals

Model Type 
text generation
Additional Notes 
This model includes full precision source code in 'safe tensors' format to generate GGUFs, GPTQ, EXL2, AWQ, HQQ and other formats.
LLM NameMN GRAND Gutenberg Lyra4 Lyra 12B MADNESS
Repository 🤗https://huggingface.co/DavidAU/MN-GRAND-Gutenberg-Lyra4-Lyra-12B-MADNESS 
Model Size12b
Required VRAM23.8 GB
Updated2026-05-10
MaintainerDavidAU
Model Typemistral
Model Files  1.3 GB: 1-of-25   1.3 GB: 2-of-25   1.0 GB: 3-of-25   0.9 GB: 4-of-25   0.9 GB: 5-of-25   0.9 GB: 6-of-25   1.0 GB: 7-of-25   0.9 GB: 8-of-25   0.9 GB: 9-of-25   0.9 GB: 10-of-25   1.0 GB: 11-of-25   0.9 GB: 12-of-25   0.9 GB: 13-of-25   0.9 GB: 14-of-25   1.0 GB: 15-of-25   0.9 GB: 16-of-25   0.9 GB: 17-of-25   0.9 GB: 18-of-25   1.0 GB: 19-of-25   0.9 GB: 20-of-25   0.9 GB: 21-of-25   0.9 GB: 22-of-25   1.0 GB: 23-of-25   0.9 GB: 24-of-25   0.8 GB: 25-of-25
Model ArchitectureMistralForCausalLM
Context Length1024000
Model Max Length1024000
Transformers Version4.43.3
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size131072
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than DavidAU/MN-GRAND-Gutenberg-Lyra4-Lyra-12B-MADNESS.

Rank the MN GRAND Gutenberg Lyra4 Lyra 12B MADNESS 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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