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Mpt 7B by mosaicml

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  Arxiv:1909.08053   Arxiv:2010.04245   Arxiv:2108.12409   Arxiv:2205.14135   Arxiv:2302.06675   Arxiv:2302.13971   Autotrain compatible   Composer   Custom code   Dataset:allenai/s2orc   Dataset:bigcode/the-stack   Dataset:c4   Dataset:mc4 Dataset:togethercomputer/redpa...   Llm-foundry   Mosaicml   Mpt   Pytorch   Region:us   Sharded   Streamingdatasets
Model Card on HF 🤗: https://huggingface.co/mosaicml/mpt-7b 

Mpt 7B Benchmarks

MMLU Pro: 2.29
GPQA: 1.34
MUSR: 2.9
BBH: 6.55
IFEval: 21.52 vs 88 (so35)-75.5%
ARC: 59.6 vs 96.7 (so35)-38.4%
HellaSwag: 75 vs 95.3 (gpt4)-21.3%
MMLU: 27.5 vs 88.3 (so35)-68.9%
TruthfulQA: 33.44 vs 59 (gpt4)-43.3%
WinoGrande: 72.14 vs 87.5 (gpt4)-17.6%
GSM8K: 9.1 vs 96.4 (so35)-90.6%
OpenCompas: 37.4 vs 73.3 (gpt4)-49%
Exam: 35.7 vs 77.2 (gpt4)-53.8%
Language: 31.9 vs 62 (gpt4)-48.5%
Knowledge: 43.4 vs 73.5 (gpt4)-41%
Understand: 34.7 vs 70 (gpt4)-50.4%
Reasoning: 38.7 vs 74.4 (gpt4)-48%
MATH Lvl 5: 1.59
LLME Score: 0.22653
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mpt 7B (mosaicml/mpt-7b)
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Mpt 7B Parameters and Internals

Model Type 
decoder-style transformer
Use Cases 
Areas:
research, commercial applications
Limitations:
Not intended for deployment without finetuning, Can produce factually incorrect output
Training Details 
Data Sources:
mc4, c4, togethercomputer/RedPajama-Data-1T, bigcode/the-stack, allenai/s2orc
Data Volume:
1T tokens
Methodology:
Pretrained from scratch on English text and code using the MosaicML LLM codebase.
Context Length:
2048
Training Time:
9.5 days
Hardware Used:
440 A100-40GB GPUs
Model Architecture:
Modified from standard transformer with FlashAttention and ALiBi, no positional embeddings.
LLM NameMpt 7B
Repository 🤗https://huggingface.co/mosaicml/mpt-7b 
Model Size7b
Required VRAM13.3 GB
Updated2025-09-23
Maintainermosaicml
Model Typempt
Model Files  9.9 GB: 1-of-2   3.4 GB: 2-of-2
Model ArchitectureMPTForCausalLM
Licenseapache-2.0
Model Max Length2048
Transformers Version4.28.1
Tokenizer ClassGPTNeoXTokenizer
Vocabulary Size50432
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than mosaicml/mpt-7b.

Rank the Mpt 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  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Release v20241124
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