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Einstein V4 7B by Weyaxi

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Einstein V4 7B Benchmarks

MMLU Pro: 13.99
GPQA: 4.25
MUSR: 19.02
BBH: 14.3
IFEval: 47.08 vs 88 (so35)-46.5%
ARC: 64.68 vs 96.7 (so35)-33.1%
HellaSwag: 83.75 vs 95.3 (gpt4)-12.1%
MMLU: 62.31 vs 88.3 (so35)-29.4%
TruthfulQA: 55.15 vs 59 (gpt4)-6.5%
WinoGrande: 76.24 vs 87.5 (gpt4)-12.9%
GSM8K: 57.62 vs 96.4 (so35)-40.2%
MATH Lvl 5: 1.74
LLME Score: 0.26687
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Einstein V4 7B Parameters and Internals

LLM NameEinstein V4 7B
Repository 🤗https://huggingface.co/Weyaxi/Einstein-v4-7B 
Base Model(s)  mistralai/Mistral-7B-v0.1   mistralai/Mistral-7B-v0.1
Model Size7b
Required VRAM14.4 GB
Updated2024-10-30
MaintainerWeyaxi
Model Typemistral
Model Files  14.5 GB   4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3   0.0 GB
Supported Languagesen
Model ArchitectureMistralForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.38.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32002
Torch Data Typebfloat16
Einstein V4 7B (Weyaxi/Einstein-v4-7B)

Quantized Models of the Einstein V4 7B

Model
Likes
Downloads
VRAM
Einstein V4 7B AWQ144 GB

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Boptruth Agatha 7B128K / 14.4 GB6670
Note: green Score (e.g. "73.2") means that the model is better than Weyaxi/Einstein-v4-7B.

Rank the Einstein V4 7B 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  
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Release v2024072803
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