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Mpt 7B Instruct Base by P1ayer-1

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Mpt 7B Instruct Base is an open-source language model by P1ayer-1. Features: 7b LLM, VRAM: 26.5GB, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.08.

  Arxiv:1909.08053   Arxiv:2010.04245   Arxiv:2108.12409   Arxiv:2205.14135   Arxiv:2302.06675   Arxiv:2302.13971   Composer   Custom code   Dataset:allenai/s2orc   Dataset:bigcode/the-stack   Dataset:c4   Dataset:mc4 Dataset:togethercomputer/redpa...   Instruct   Llm-foundry   Mosaicml   Mpt   Pytorch   Region:us   Sharded   Streamingdatasets
Model Card on HF 🤗: https://huggingface.co/P1ayer-1/mpt-7b-instruct-base 

Mpt 7B Instruct Base Benchmarks

LLME Score: 0.08323
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 Base (P1ayer-1/mpt-7b-instruct-base)
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Mpt 7B Instruct Base Parameters and Internals

Model Type 
decoder-style transformer
Use Cases 
Areas:
Research, Commercial applications, Story writing, Instruction following, Chatbot dialogue generation
Applications:
Fictional story writing with longer contexts, Instruction following, Dialogue chatbot applications
Primary Use Cases:
Reading and writing fictional stories, Instruction following tasks, Chatbot dialogue generation
Limitations:
Not intended for deployment without fine-tuning, Can produce factually incorrect outputs
Considerations:
Not to be used for human-facing interactions without guardrails.
Additional Notes 
MPT models include optimizations such as FlashAttention and ALiBi for improved training and inference efficiencies.
Supported Languages 
English (High proficiency)
Training Details 
Data Sources:
mc4, c4, togethercomputer/RedPajama-Data-1T, bigcode/the-stack, allenai/s2orc
Data Volume:
1T tokens
Methodology:
Pre-trained, Modified Transformers with ALiBi and FlashAttention
Context Length:
2048
Training Time:
9.5 days
Hardware Used:
440 A100-40GB GPUs
Model Architecture:
Decoder-style transformer with FlashAttention and ALiBi
Input Output 
Input Format:
Tokenized sequences with EleutherAI/gpt-neox-20b tokenizer
Accepted Modalities:
text
Output Format:
Generated sequences
LLM NameMpt 7B Instruct Base
Repository 🤗https://huggingface.co/P1ayer-1/mpt-7b-instruct-base 
Model Size7b
Required VRAM26.5 GB
Updated2026-04-11
MaintainerP1ayer-1
Model Typempt
Instruction-BasedYes
Model Files  9.9 GB: 1-of-3   9.9 GB: 2-of-3   6.7 GB: 3-of-3
Model ArchitectureMPTForCausalLM
Licenseapache-2.0
Transformers Version4.28.1
Tokenizer ClassGPTNeoXTokenizer
Vocabulary Size50279
Torch Data Typefloat32

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Sea Lion 7B Instruct0K / 15 GB20823
Sea Lion 7B Instruct Research0K / 15 GB1114
Results0K / 13.3 GB70
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...7B 8K Instruct Peft Compatible0K / 13.3 GB01
Vigogne Mpt 7B Instruct0K / 13.4 GB50
Note: green Score (e.g. "73.2") means that the model is better than P1ayer-1/mpt-7b-instruct-base.

Rank the Mpt 7B Instruct Base 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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