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Upstage Llama 2 70B Instruct V2 GGUF by TheBloke

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Upstage Llama 2 70B Instruct V2 GGUF is an open-source language model by TheBloke. Features: 70b LLM, VRAM: 29.3GB, License: llama2, Quantized, Instruction-Based, LLM Explorer Score: 0.09.

Base model:quantized:upstage/s... Base model:upstage/solar-0-70b...   En   Gguf   Instruct   Instruction   Llama   Llama2   Quantized   Region:us   Upstage
Model Card on HF 🤗: https://huggingface.co/TheBloke/Upstage-Llama-2-70B-instruct-v2-GGUF 

Upstage Llama 2 70B Instruct V2 GGUF Benchmarks

LLME Score: 0.09497
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Upstage Llama 2 70B Instruct V2 GGUF (TheBloke/Upstage-Llama-2-70B-instruct-v2-GGUF)
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Upstage Llama 2 70B Instruct V2 GGUF Parameters and Internals

Model Type 
llama
Use Cases 
Areas:
research, commercial applications
Additional Notes 
The model can handle more than 10k input tokens due to `rope_scaling` feature.
Supported Languages 
English (proficient)
Training Details 
Data Sources:
Orca-style dataset, Alpaca-style dataset
Context Length:
10000
Hardware Used:
A100x8 * 4
Model Architecture:
LLaMA-2
Input Output 
Input Format:
"### User:\n{prompt}\n\n### Assistant:\n"
Accepted Modalities:
text
LLM NameUpstage Llama 2 70B Instruct V2 GGUF
Repository 🤗https://huggingface.co/TheBloke/Upstage-Llama-2-70B-instruct-v2-GGUF 
Model NameLlama 2 70B Instruct v2
Model CreatorUpstage
Base Model(s)  upstage/Llama-2-70b-instruct-v2   upstage/Llama-2-70b-instruct-v2
Model Size70b
Required VRAM29.3 GB
Updated2026-04-24
MaintainerTheBloke
Model Typellama
Instruction-BasedYes
Model Files  29.3 GB   36.1 GB   33.2 GB   29.9 GB   38.9 GB   41.4 GB   39.1 GB   47.5 GB   48.8 GB   47.5 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureAutoModel
Licensellama2

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Upstage-Llama-2-70B-instruct-v2-GGUF.

Rank the Upstage Llama 2 70B Instruct V2 GGUF 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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