Scarlett 7B GGML by TheBloke

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Base model:ajibawa-2023/scarle... Base model:finetune:ajibawa-20...   En   Ggml   Llama   Quantized   Region:us

Scarlett 7B GGML Benchmarks

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

Model Type 
llama
Use Cases 
Applications:
Philosophy, Advice, Jokes
Primary Use Cases:
Answering questions, Providing recommendations, Philosophical discussions, Personal relationships, Helping with decision making
Limitations:
Will not be involved in any kind of role play
Additional Notes 
Scarlett is trained on more than 10000 sets of conversations, each set having 10~15 conversations. Heavily inspired by Eric Hartford's Samantha.
Training Details 
Methodology:
DeepSpeed codebase was used for training purpose. This was trained on Llama-1 by Meta.
Hardware Used:
4 x A100 80GB
LLM NameScarlett 7B GGML
Repository ๐Ÿค—https://huggingface.co/TheBloke/Scarlett-7B-GGML 
Model NameScarlett 7B
Model CreatorFeynman Innovations
Base Model(s)  Scarlett 7B   ajibawa-2023/scarlett-7b
Model Size7b
Required VRAM2.9 GB
Updated2025-09-20
MaintainerTheBloke
Model Typellama
Model Files  2.9 GB   3.6 GB   3.3 GB   3.0 GB   3.8 GB   4.2 GB   4.1 GB   3.8 GB   4.7 GB   5.1 GB   4.8 GB   4.7 GB   5.5 GB   7.1 GB
Supported Languagesen
GGML QuantizationYes
Quantization Typeggml
Model ArchitectureAutoModel
Licenseother

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

Rank the Scarlett 7B GGML 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124