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Mergekit Slerp Lvhhlmq by mergekit-community

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Mergekit Slerp Lvhhlmq is an open-source language model by mergekit-community. Features: 2b LLM, VRAM: 5GB, Context: 8K, Merged, LLM Explorer Score: 0.13.

  Merged Model   Base model:beomi/gemma-ko-2b   Base model:unsloth/gemma-2b   Endpoints compatible   Gemma   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/mergekit-community/mergekit-slerp-lvhhlmq 

Mergekit Slerp Lvhhlmq Benchmarks

LLME Score: 0.12737
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mergekit Slerp Lvhhlmq (mergekit-community/mergekit-slerp-lvhhlmq)
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Mergekit Slerp Lvhhlmq Parameters and Internals

Training Details 
Methodology:
SLERP merge method
LLM NameMergekit Slerp Lvhhlmq
Repository 🤗https://huggingface.co/mergekit-community/mergekit-slerp-lvhhlmq 
Base Model(s)  Gemma Ko 2B   Gemma 2B   beomi/gemma-ko-2b   unsloth/gemma-2b
Merged ModelYes
Model Size2b
Required VRAM5 GB
Updated2026-05-26
Maintainermergekit-community
Model Typegemma
Model Files  5.0 GB: 1-of-1
Model ArchitectureGemmaForCausalLM
Context Length8192
Model Max Length8192
Transformers Version4.39.3
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typebfloat16

Quantized Models of the Mergekit Slerp Lvhhlmq

Model
Likes
Downloads
VRAM
Mergekit Slerp Lvhhlmq GGUF0251 GB

Best Alternatives to Mergekit Slerp Lvhhlmq

Best Alternatives
Context / RAM
Downloads
Likes
Gemma 1.1 2B It8K / 5.1 GB80705172
Gemma 1.1 2B It8K / 5 GB723
Codegemma 2B8K / 5.1 GB3243998
Gita SastraGPT V18K / 5.1 GB191
Caca Tinny 2B V38K / 5.1 GB41
Pandas Tutor Gemma 2B8K / 5.1 GB81
Gemma Qlora Customer Support8K / 5.1 GB230
... 2B Finetuned Sft Navarasa 2.08K / 10 GB100626
Octopus V28K / 5.1 GB1387885
Bge Reranker V2 Gemma8K / 10 GB2503184
Note: green Score (e.g. "73.2") means that the model is better than mergekit-community/mergekit-slerp-lvhhlmq.

Rank the Mergekit Slerp Lvhhlmq 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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