Meliodas 7B Dare by AurelPx

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  Merged Model   Ammarali32/multi verse model   Autotrain compatible   Base model:liminerity/m7-7b Base model:mtsair/multi verse ...   Endpoints compatible   Liminerity/m7-7b   Mistral   Region:us   Safetensors   Sharded   Tensorflow

Meliodas 7B Dare Benchmarks

Meliodas 7B Dare (AurelPx/Meliodas-7b-dare)

Meliodas 7B Dare Parameters and Internals

Model Type 
text generation
Additional Notes 
Meliodas-7b-dare is a merged model using the LazyMergekit methodology, with specific configurations including density and weight parameters applied to the merging process. It leverages models liminerity/M7-7b and ammarali32/multi_verse_model.
LLM NameMeliodas 7B Dare
Repository ๐Ÿค—https://huggingface.co/AurelPx/Meliodas-7b-dare 
Base Model(s)  M7 7B   ammarali32/multi_verse_model   liminerity/M7-7b   ammarali32/multi_verse_model
Merged ModelYes
Model Size7b
Required VRAM14.4 GB
Updated2025-02-23
MaintainerAurelPx
Model Typemistral
Model Files  2.0 GB: 1-of-8   2.0 GB: 2-of-8   1.9 GB: 3-of-8   2.0 GB: 4-of-8   1.9 GB: 5-of-8   1.9 GB: 6-of-8   1.9 GB: 7-of-8   0.8 GB: 8-of-8
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.38.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than AurelPx/Meliodas-7b-dare.

Rank the Meliodas 7B Dare 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 v20241227