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Llama 2 7B LoRA Assemble by oh-yeontaek

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  Autotrain compatible   Endpoints compatible   Llama   Lora   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/oh-yeontaek/llama-2-7B-LoRA-assemble 

Llama 2 7B LoRA Assemble Benchmarks

ARC: 57.34 vs 96.7 (so35)-40.7%
HellaSwag: 78.81 vs 95.3 (gpt4)-17.3%
MMLU: 50.75 vs 88.3 (so35)-42.5%
TruthfulQA: 53.18 vs 59 (gpt4)-9.9%
WinoGrande: 73.48 vs 87.5 (gpt4)-16%
LLME Score: 0.15516
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 2 7B LoRA Assemble (oh-yeontaek/llama-2-7B-LoRA-assemble)
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Llama 2 7B LoRA Assemble Parameters and Internals

LLM NameLlama 2 7B LoRA Assemble
Repository 🤗https://huggingface.co/oh-yeontaek/llama-2-7B-LoRA-assemble 
Model Size7b
Required VRAM13.5 GB
Updated2025-08-22
Maintaineroh-yeontaek
Model Typellama
Model Files  10.0 GB: 1-of-2   3.5 GB: 2-of-2
Model ArchitectureLlamaForCausalLM
Context Length4096
Model Max Length4096
Transformers Version4.31.0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
LoRA ModelYes
Torch Data Typefloat16

Quantized Models of the Llama 2 7B LoRA Assemble

Model
Likes
Downloads
VRAM
Llama 2 7B LoRA Assemble GGUF1652 GB
Llama 2 7B LoRA Assemble AWQ173 GB
Llama 2 7B LoRA Assemble GPTQ173 GB

Best Alternatives to Llama 2 7B LoRA Assemble

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1241024K / 16.1 GB930
1621024K / 16.1 GB600
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Note: green Score (e.g. "73.2") means that the model is better than oh-yeontaek/llama-2-7B-LoRA-assemble.

Rank the Llama 2 7B LoRA Assemble 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
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