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Mpt 7B Q8 by Abzu

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Mpt 7B Q8 is an open-source language model by Abzu. Features: 7b LLM, VRAM: 6.9GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.11, Arc: 47.4, HellaSwag: 77.4, MMLU: 42.6, GSM8K: 8.3.

  Arxiv:1909.08053   Arxiv:2010.04245   Arxiv:2108.12409   Arxiv:2205.14135   Arxiv:2302.06675   Arxiv:2302.13971   8-bit   Composer   Custom code   Dataset:allenai/s2orc   Dataset:bigcode/the-stack   Dataset:c4   Dataset:mc4 Dataset:togethercomputer/redpa...   Llm-foundry   Mosaicml   Mpt   Q8   Quantized   Region:us   Safetensors   Streamingdatasets
Model Card on HF 🤗: https://huggingface.co/Abzu/mpt-7b-q8 

Mpt 7B Q8 Benchmarks

ARC: 47.35 vs 96.7 (so35)-51%
HellaSwag: 77.4 vs 95.3 (gpt4)-18.8%
MMLU: 42.58 vs 88.3 (so35)-51.8%
GSM8K: 8.34 vs 96.4 (so35)-91.3%
LLME Score: 0.1112
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mpt 7B Q8 (Abzu/mpt-7b-q8)
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Mpt 7B Q8 Parameters and Internals

Model Type 
decoder-style transformer
Additional Notes 
Utilizes ALiBi to handle extremely long inputs beyond its training context length. The model can be utilized with HuggingFace's Transformers library.
Supported Languages 
English (Unknown)
Training Details 
Data Sources:
mc4, c4, togethercomputer/RedPajama-Data-1T, bigcode/the-stack, allenai/s2orc
Data Volume:
1T tokens
Methodology:
Transformer architecture modifications including ALiBi and FlashAttention
Context Length:
2048
Training Time:
9.5 days
Hardware Used:
440 A100-40GB GPUs
Model Architecture:
Decoder-only transformer using FlashAttention and ALiBi
Input Output 
Input Format:
Text
Accepted Modalities:
Text
Output Format:
Text
LLM NameMpt 7B Q8
Repository 🤗https://huggingface.co/Abzu/mpt-7b-q8 
Base Model(s)  Mpt 7B 8K   mosaicml/mpt-7b-8k
Model Size7b
Required VRAM6.9 GB
Updated2026-05-23
MaintainerAbzu
Model Typempt
Model Files  6.9 GB
Quantization Typeq8
Model ArchitectureMPTForCausalLM
Licenseapache-2.0
Model Max Length2048
Transformers Version4.30.2
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 Abzu/mpt-7b-q8.

Rank the Mpt 7B Q8 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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