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Upstage Llama 2 70B Instruct V2 GGUF by TheBloke

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Base model:quantized:upstage/s... Base model:upstage/solar-0-70b...   En   Gguf   Instruct   Instruction   Llama   Llama2   Quantized   Region:us   Upstage

Upstage Llama 2 70B Instruct V2 GGUF Benchmarks

LLME Score: 0.14693
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 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
Updated2024-11-21
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
Upstage Llama 2 70B Instruct V2 GGUF (TheBloke/Upstage-Llama-2-70B-instruct-v2-GGUF)

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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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Release v20241110
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