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MemGPT DPO MoE Test by starsnatched

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Model Card on HF 🤗: https://huggingface.co/starsnatched/MemGPT-DPO-MoE-test 

MemGPT DPO MoE Test Benchmarks

LLME Score: 0.13907
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MemGPT DPO MoE Test (starsnatched/MemGPT-DPO-MoE-test)
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MemGPT DPO MoE Test Parameters and Internals

Model Type 
language model, transformer decoder
Use Cases 
Primary Use Cases:
base model for MemGPT agents
Limitations:
unreliable, unsafe, or biased behaviors
Considerations:
Double-check the results produced.
Supported Languages 
en (primary)
Training Details 
Methodology:
Mixture of Experts (MoE) with 2 experts per token.
Context Length:
8192
Hardware Used:
2x A100 80GB GPUs
Model Architecture:
transformer decoder
Input Output 
Input Format:
ChatML
Accepted Modalities:
text
LLM NameMemGPT DPO MoE Test
Repository 🤗https://huggingface.co/starsnatched/MemGPT-DPO-MoE-test 
Model Size12.9b
Required VRAM25.8 GB
Updated2024-10-25
Maintainerstarsnatched
Model Typemixtral
Instruction-BasedYes
Model Files  5.0 GB: 1-of-6   4.9 GB: 2-of-6   5.0 GB: 3-of-6   5.0 GB: 4-of-6   4.9 GB: 5-of-6   1.0 GB: 6-of-6
Supported Languagesen
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.2
Tokenizer ClassLlamaTokenizer
Padding Token<s>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than starsnatched/MemGPT-DPO-MoE-test.

Rank the MemGPT DPO MoE Test Capabilities

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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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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