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Calme 4x7B MoE V0.1 by MaziyarPanahi

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  7b   Autotrain compatible   Calme   Conversational   Generated from trainer   Mistral   Mixtral   Moe   Region:us   Safetensors   Sharded   Tensorflow

Calme 4x7B MoE V0.1 Benchmarks

MMLU Pro: 22.85
GPQA: 4.25
MUSR: 10.62
BBH: 31.26
IFEval: 43.15 vs 88 (so35)-51%
ARC: 72.53 vs 96.7 (so35)-25%
HellaSwag: 88.6 vs 95.3 (gpt4)-7%
MMLU: 64.57 vs 88.3 (so35)-26.9%
TruthfulQA: 72.86 vs 59 (gpt4)23.5%
WinoGrande: 83.5 vs 87.5 (gpt4)-4.6%
GSM8K: 71.11 vs 96.4 (so35)-26.2%
MATH Lvl 5: 7.4
LLME Score: 0.32042
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Calme 4x7B MoE V0.1 Parameters and Internals

LLM NameCalme 4x7B MoE V0.1
Repository 🤗https://huggingface.co/MaziyarPanahi/Calme-4x7B-MoE-v0.1 
Model NameCalme-4x7B-MoE-v0.1
Model CreatorMaziyarPanahi
Model Size24.2b
Required VRAM48.3 GB
Updated2024-09-07
MaintainerMaziyarPanahi
Model Typemixtral
Model Files  9.9 GB: 1-of-5   9.9 GB: 2-of-5   10.0 GB: 3-of-5   10.0 GB: 4-of-5   8.5 GB: 5-of-5
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.2
Tokenizer ClassLlamaTokenizer
Padding Token<s>
Vocabulary Size32000
Torch Data Typebfloat16
Calme 4x7B MoE V0.1 (MaziyarPanahi/Calme-4x7B-MoE-v0.1)

Quantized Models of the Calme 4x7B MoE V0.1

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VRAM
Calme 4x7B MoE V0.1 GGUF01498 GB

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Note: green Score (e.g. "73.2") means that the model is better than MaziyarPanahi/Calme-4x7B-MoE-v0.1.

Rank the Calme 4x7B MoE V0.1 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 v2024072803
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