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ELYZA Japanese Llama 2 7B Fast Instruct GPTQ by dahara1

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  Arxiv:2307.09288   4bit   Autotrain compatible   En   Gptq   Instruct   Ja   Llama   Quantized   Region:us   Safetensors

ELYZA Japanese Llama 2 7B Fast Instruct GPTQ Benchmarks

ARC: 53.16 vs 96.7 (so35)-45%
HellaSwag: 78.25 vs 95.3 (gpt4)-17.9%
MMLU: 47.07 vs 88.3 (so35)-46.7%
TruthfulQA: 39.08 vs 59 (gpt4)-33.8%
WinoGrande: 73.24 vs 87.5 (gpt4)-16.3%
GSM8K: 7.88 vs 96.4 (so35)-91.8%
LLME Score: 0.18218
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

ELYZA Japanese Llama 2 7B Fast Instruct GPTQ Parameters and Internals

LLM NameELYZA Japanese Llama 2 7B Fast Instruct GPTQ
Repository 🤗https://huggingface.co/dahara1/ELYZA-japanese-Llama-2-7b-fast-instruct-GPTQ 
Base Model(s)  ...A Japanese Llama 2 7B Instruct   elyza/ELYZA-japanese-Llama-2-7b-instruct
Model Size7b
Required VRAM4.1 GB
Updated2024-10-18
Maintainerdahara1
Model Typellama
Instruction-BasedYes
Model Files  4.1 GB   4.1 GB
Supported Languagesja en
GPTQ QuantizationYes
Quantization Typegptq|4bit
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.35.0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size45043
Torch Data Typefloat16
ELYZA Japanese Llama 2 7B Fast Instruct GPTQ (dahara1/ELYZA-japanese-Llama-2-7b-fast-instruct-GPTQ)

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Note: green Score (e.g. "73.2") means that the model is better than dahara1/ELYZA-japanese-Llama-2-7b-fast-instruct-GPTQ.

Rank the ELYZA Japanese Llama 2 7B Fast Instruct GPTQ 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  
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Release v2024072803
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