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Mpt 7B Instruct by gl198976

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  Arxiv:2010.04245   Arxiv:2108.12409   Arxiv:2205.14135   Composer   Custom code   Dataset:mosaicml/dolly hhrlhf   Instruct   Llm-foundry   Mosaicml   Mpt   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/gl198976/mpt-7b-instruct 

Mpt 7B Instruct Benchmarks

LLME Score: 0.08133
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mpt 7B Instruct (gl198976/mpt-7b-instruct)
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Mpt 7B Instruct Parameters and Internals

Model Type 
Instruction following, Short-form generation
Additional Notes 
Trained with EleutherAI/gpt-neox-20b tokenizer
Training Details 
Data Sources:
Databricks Dolly-15k, Anthropic Helpful and Harmless (HH-RLHF)
Methodology:
Finetuning
Context Length:
2048
Model Architecture:
Modified decoder-only transformer
Input Output 
Accepted Modalities:
Text
Performance Tips:
Use devices such as CUDA for optimized performance with FlashAttention, ALiBi to increase max sequence length.
LLM NameMpt 7B Instruct
Repository 🤗https://huggingface.co/gl198976/mpt-7b-instruct 
Model Size7b
Required VRAM13.3 GB
Updated2025-12-22
Maintainergl198976
Model Typempt
Instruction-BasedYes
Model Files  9.9 GB: 1-of-2   3.4 GB: 2-of-2   9.9 GB: 1-of-2   3.4 GB: 2-of-2
Model ArchitectureMPTForCausalLM
Licensecc-by-sa-3.0
Model Max Length2048
Transformers Version4.28.1
Tokenizer ClassGPTNeoXTokenizer
Vocabulary Size50432
Torch Data Typebfloat16

Best Alternatives to Mpt 7B Instruct

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Context / RAM
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Mpt 7B Chat0K / 13.3 GB80920518
Mpt 7B Instruct0K / 13.3 GB7946470
Mpt 7B Int8 Ov0K / 0 GB130
Mpt 7B 8K Instruct0K / 13.3 GB201227
Sea Lion 7B Instruct0K / 15 GB20823
Sea Lion 7B Instruct Research0K / 15 GB1114
Results0K / 13.3 GB70
Mpt 7B 8K Chat Sharded Bf160K / 13.4 GB61
...7B 8K Instruct Peft Compatible0K / 13.3 GB01
Vigogne Mpt 7B Instruct0K / 13.4 GB150
Note: green Score (e.g. "73.2") means that the model is better than gl198976/mpt-7b-instruct.

Rank the Mpt 7B Instruct 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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