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Mergekit Della Linear Vmeykci by Sakalti

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Mergekit Della Linear Vmeykci is an open-source language model by Sakalti. Features: 7b LLM, VRAM: 16.2GB, Context: 986K, Instruction-Based, Merged, LLM Explorer Score: 0.18.

  Merged Model Base model:axcxept/qwen2.5-mat... Base model:bunnycore/qwen2.5-7...   Conversational   Endpoints compatible   Instruct   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Sakalti/mergekit-della_linear-vmeykci 

Mergekit Della Linear Vmeykci Benchmarks

LLME Score: 0.18174
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mergekit Della Linear Vmeykci (Sakalti/mergekit-della_linear-vmeykci)
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Mergekit Della Linear Vmeykci Parameters and Internals

LLM NameMergekit Della Linear Vmeykci
Repository 🤗https://huggingface.co/Sakalti/mergekit-della_linear-vmeykci 
Base Model(s)  AXCXEPT/Qwen2.5-Math-7B-Instruct-jp-EZO_OREO   bunnycore/Qwen2.5-7B-RRP-1M   AXCXEPT/Qwen2.5-Math-7B-Instruct-jp-EZO_OREO   bunnycore/Qwen2.5-7B-RRP-1M
Merged ModelYes
Model Size7b
Required VRAM16.2 GB
Updated2026-05-20
MaintainerSakalti
Model Typeqwen2
Instruction-BasedYes
Model Files  1.1 GB: 1-of-30   1.1 GB: 2-of-30   0.5 GB: 3-of-30   0.5 GB: 4-of-30   0.5 GB: 5-of-30   0.5 GB: 6-of-30   0.5 GB: 7-of-30   0.5 GB: 8-of-30   0.5 GB: 9-of-30   0.5 GB: 10-of-30   0.5 GB: 11-of-30   0.5 GB: 12-of-30   0.5 GB: 13-of-30   0.5 GB: 14-of-30   0.5 GB: 15-of-30   0.5 GB: 16-of-30   0.5 GB: 17-of-30   0.5 GB: 18-of-30   0.5 GB: 19-of-30   0.5 GB: 20-of-30   0.5 GB: 21-of-30   0.5 GB: 22-of-30   0.5 GB: 23-of-30   0.5 GB: 24-of-30   0.5 GB: 25-of-30   0.5 GB: 26-of-30   0.5 GB: 27-of-30   0.5 GB: 28-of-30   0.5 GB: 29-of-30   0.5 GB: 30-of-30
Model ArchitectureQwen2ForCausalLM
Context Length1010000
Model Max Length1010000
Transformers Version4.46.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151665
Torch Data Typefloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than Sakalti/mergekit-della_linear-vmeykci.

Rank the Mergekit Della Linear Vmeykci 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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