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Mpt 7B Instruct by mosaicml

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  7946   
  Arxiv:2010.04245   Arxiv:2108.12409   Arxiv:2205.14135   Autotrain compatible   Composer   Custom code   Dataset:mosaicml/dolly hhrlhf   Instruct   Llm-foundry   Mosaicml   Mpt   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/mosaicml/mpt-7b-instruct 

Mpt 7B Instruct Benchmarks

ARC: 38.4 vs 96.7 (so35)-60.3%
HellaSwag: 75.8 vs 95.3 (gpt4)-20.5%
MMLU: 30.6 vs 88.3 (so35)-65.3%
TruthfulQA: 35.08 vs 59 (gpt4)-40.5%
WinoGrande: 70.48 vs 87.5 (gpt4)-19.5%
GSM8K: 7.8 vs 96.4 (so35)-91.9%
OpenCompas: 36.8 vs 73.3 (gpt4)-49.8%
Exam: 30.2 vs 77.2 (gpt4)-60.9%
Language: 32 vs 62 (gpt4)-48.4%
Knowledge: 40.8 vs 73.5 (gpt4)-44.5%
Understand: 37.5 vs 70 (gpt4)-46.4%
Reasoning: 38.7 vs 74.4 (gpt4)-48%
LLME Score: 0.17406
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 (mosaicml/mpt-7b-instruct)
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Mpt 7B Instruct Parameters and Internals

Model Type 
Instruction following, Text generation
Use Cases 
Areas:
Research, Commercial applications
Primary Use Cases:
Short-form instruction following
Limitations:
Can produce factually incorrect or offensive outputs
Considerations:
Should not be relied on to produce factually accurate information
Additional Notes 
Uses a custom MPT architecture and requires `trust_remote_code=True` in some processes.
Training Details 
Data Sources:
databricks/databricks-dolly-15k, Anthropic/hh-rlhf
Methodology:
Decoder-only transformer architecture with modifications such as FlashAttention, ALiBi, no positional embeddings, no biases
Context Length:
2048
Training Time:
2.3 hours
Hardware Used:
8 A100-40GB GPUs
Model Architecture:
Modified decoder-only transformer with 32 layers and 32 heads, d_model: 4096, vocab size: 50432
Input Output 
Input Format:
Formatted prompts using instruction and response keys from dolly-15k format
Accepted Modalities:
Text
Output Format:
Textual response
Performance Tips:
Use torch.autocast for lower precision runs. Increase max sequence length with ALiBi.
LLM NameMpt 7B Instruct
Repository 🤗https://huggingface.co/mosaicml/mpt-7b-instruct 
Model Size7b
Required VRAM13.3 GB
Updated2025-09-23
Maintainermosaicml
Model Typempt
Instruction-BasedYes
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

Quantized Models of the Mpt 7B Instruct

Model
Likes
Downloads
VRAM
Mpt 7B Instruct Q82226 GB

Best Alternatives to Mpt 7B Instruct

Best Alternatives
Context / RAM
Downloads
Likes
Mpt 7B Chat0K / 13.3 GB80920518
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 GB161
Vigogne Mpt 7B Instruct0K / 13.4 GB150
...pt 7B Instruct Peft Compatible0K / 13.3 GB220
Note: green Score (e.g. "73.2") means that the model is better than mosaicml/mpt-7b-instruct.

Rank the Mpt 7B Instruct Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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