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EXAONE-3.0-7.8B-Instruct-GGUF

Original Model

LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct

Run with LlamaEdge

  • LlamaEdge version: coming soon
  • Prompt template

    • Prompt type: exaone-chat

    • Prompt string

      [|system|]system_prompt_text[|endofturn|]
      [|user|]user_1st_turn_text
      [|assistant|]assistant_1st_turn_text[|endofturn|]
      [|user|]user_2nd_turn_text
      [|assistant|]assistant_2nd_turn_text[|endofturn|]
      
  • Context size: 4096

  • Run as LlamaEdge service

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:EXAONE-3.0-7.8B-Instruct-Q5_K_M.gguf \
        llama-api-server.wasm \
        --prompt-template exaone-chat \
        --ctx-size 4096 \
        --model-name EXAONE-3.0-7.8B-Instruct
    
  • Run as LlamaEdge command app

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:EXAONE-3.0-7.8B-Instruct-Q5_K_M.gguf \
      llama-chat.wasm \
      --prompt-template exaone-chat \
      --ctx-size 4096
    

Quantized GGUF Models

Name Quant method Bits Size Use case
EXAONE-3.0-7.8B-Instruct-Q2_K.gguf Q2_K 2 3.05 GB smallest, significant quality loss - not recommended for most purposes
EXAONE-3.0-7.8B-Instruct-Q3_K_L.gguf Q3_K_L 3 4.19 GB small, substantial quality loss
EXAONE-3.0-7.8B-Instruct-Q3_K_M.gguf Q3_K_M 3 3.88 GB very small, high quality loss
EXAONE-3.0-7.8B-Instruct-Q3_K_S.gguf Q3_K_S 3 3.53 GB very small, high quality loss
EXAONE-3.0-7.8B-Instruct-Q4_0.gguf Q4_0 4 4.51 GB legacy; small, very high quality loss - prefer using Q3_K_M
EXAONE-3.0-7.8B-Instruct-Q4_K_M.gguf Q4_K_M 4 4.77 GB medium, balanced quality - recommended
EXAONE-3.0-7.8B-Instruct-Q4_K_S.gguf Q4_K_S 4 4.54 GB small, greater quality loss
EXAONE-3.0-7.8B-Instruct-Q5_0.gguf Q5_0 5 5.44 GB legacy; medium, balanced quality - prefer using Q4_K_M
EXAONE-3.0-7.8B-Instruct-Q5_K_M.gguf Q5_K_M 5 5.57 GB large, very low quality loss - recommended
EXAONE-3.0-7.8B-Instruct-Q5_K_S.gguf Q5_K_S 5 5.44 GB large, low quality loss - recommended
EXAONE-3.0-7.8B-Instruct-Q6_K.gguf Q6_K 6 6.42 GB very large, extremely low quality loss
EXAONE-3.0-7.8B-Instruct-Q8_0.gguf Q8_0 8 8.31 GB very large, extremely low quality loss - not recommended
EXAONE-3.0-7.8B-Instruct-f16.gguf f16 16 15.6 GB

Quantized with llama.cpp b3807.

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Inference Examples
Inference API (serverless) has been turned off for this model.

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