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 ๐Ÿค—: https://huggingface.co/mosaicml/mpt-7b 

Mpt 7B Benchmarks

Mpt 7B (mosaicml/mpt-7b)

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 ๐Ÿค—https://huggingface.co/mosaicml/mpt-7b 
Model Size7b
Required VRAM13.3 GB
Updated2024-12-21
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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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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217