MAmmoTH 7B GGUF by TheBloke

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  Arxiv:2309.05653 Base model:quantized:tiger-lab... Base model:tiger-lab/mammoth-7...   Dataset:tiger-lab/mathinstruct   En   Gguf   Llama   Quantized   Region:us

MAmmoTH 7B GGUF Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MAmmoTH 7B GGUF (TheBloke/MAmmoTH-7B-GGUF)
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MAmmoTH 7B GGUF Parameters and Internals

Model Type 
llama
Use Cases 
Areas:
Research, Educational Software, Tutoring Systems
Primary Use Cases:
Solving general math problems
Limitations:
Performance may vary based on the complexity and specifics of the math problem. Not all mathematical fields are comprehensively covered.
Additional Notes 
The model can generate both a chain of thought (CoT) rationale and a program of thought (PoT) rationale, providing a comprehensive solution to a given math problem.
Training Details 
Data Sources:
MathInstruct Dataset
Methodology:
Models are fine-tuned with the MathInstruct dataset using original Llama-2 and Code Llama models as base models.
LLM NameMAmmoTH 7B GGUF
Repository ๐Ÿค—https://huggingface.co/TheBloke/MAmmoTH-7B-GGUF 
Model NameMAmmoTH 7B
Model CreatorTIGER-Lab
Base Model(s)  MAmmoTH 7B   TIGER-Lab/MAmmoTH-7B
Model Size7b
Required VRAM2.8 GB
Updated2025-09-13
MaintainerTheBloke
Model Typellama
Model Files  2.8 GB   3.6 GB   3.3 GB   3.0 GB   3.8 GB   4.1 GB   3.9 GB   4.7 GB   4.8 GB   4.7 GB   5.5 GB   7.2 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureAutoModel
Licensemit

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/MAmmoTH-7B-GGUF.

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124