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MBX 7B V3 by flemmingmiguel

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  Autotrain compatible   Endpoints compatible   Flemmingmiguel/mbx-7b   Flemmingmiguel/mbx-7b-v3   Lazymergekit   Merge   Mergekit   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/flemmingmiguel/MBX-7B-v3 

MBX 7B V3 Benchmarks

ARC: 74.15 vs 96.7 (so35)-23.3%
HellaSwag: 88.91 vs 95.3 (gpt4)-6.7%
MMLU: 65.06 vs 88.3 (so35)-26.3%
TruthfulQA: 71.87 vs 59 (gpt4)21.8%
WinoGrande: 85.56 vs 87.5 (gpt4)-2.2%
GSM8K: 70.28 vs 96.4 (so35)-27.1%
LLME Score: 0.19833
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MBX 7B V3 (flemmingmiguel/MBX-7B-v3)

MBX 7B V3 Parameters and Internals

Model Type 
merge
Additional Notes 
Quantized GGUF version available.
Training Details 
Methodology:
LazyMergekit merging of models
Input Output 
Output Format:
text
LLM NameMBX 7B V3
Repository 🤗https://huggingface.co/flemmingmiguel/MBX-7B-v3 
Model Size7b
Required VRAM14.4 GB
Updated2024-12-23
Maintainerflemmingmiguel
Model Typemistral
Model Files  9.9 GB: 1-of-2   4.5 GB: 2-of-2
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than flemmingmiguel/MBX-7B-v3.

Rank the MBX 7B V3 Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217
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