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metadata
license: other
license_name: tongyi-qianwen
license_link: https://huggingface.co/Qwen/Qwen1.5-110B-Chat/blob/main/LICENSE
model_name: Qwen1.5-110B-Chat
arxiv: 2307.09288
base_model: Qwen/Qwen1.5-110B-Chat
inference: false
model_creator: Qwen
pipeline_tag: text-generation
quantized_by: Second State Inc.
language:
  - en
tags:
  - chat

Qwen1.5-110B-Chat-GGUF

Original Model

Qwen/Qwen1.5-110B-Chat

Run with LlamaEdge

  • LlamaEdge version: coming soon

  • Prompt template

    • Prompt type: chatml

    • Prompt string

      <|im_start|>system
      {system_message}<|im_end|>
      <|im_start|>user
      {prompt}<|im_end|>
      <|im_start|>assistant
      
  • Context size: 8192

  • Run as LlamaEdge service

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Qwen1.5-110B-Chat-Q2_K.gguf \
      llama-api-server.wasm \
      --prompt-template chatml \
      --ctx-size 8192 \
      --model-name qwen1.5-110b-chat
    
  • Run as LlamaEdge command app

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Qwen1.5-110B-Chat-Q2_K.gguf \
      llama-chat.wasm \
      --prompt-template chatml
    

Quantized GGUF Models

Name Quant method Bits Size Use case
Qwen1.5-110B-Chat-Q2_K.gguf Q2_K 2 41.2 GB smallest, significant quality loss - not recommended for most purposes
Qwen1.5-110B-Chat-Q3_K_M-00001-of-00002.gguf Q3_K_M 3 32.2 GB very small, high quality loss
Qwen1.5-110B-Chat-Q3_K_M-00002-of-00002.gguf Q3_K_M 3 21.5 GB very small, high quality loss
Qwen1.5-110B-Chat-Q4_K_M-00001-of-00003.gguf Q4_K_M 4 32 GB medium, balanced quality - recommended
Qwen1.5-110B-Chat-Q4_K_M-00002-of-00003.gguf Q4_K_M 4 32.1 GB medium, balanced quality - recommended
Qwen1.5-110B-Chat-Q4_K_M-00003-of-00003.gguf Q4_K_M 4 3.09 GB medium, balanced quality - recommended
Qwen1.5-110B-Chat-Q5_K_M-00001-of-00003.gguf Q5_K_M 5 32.1 GB large, very low quality loss - recommended
Qwen1.5-110B-Chat-Q5_K_M-00002-of-00003.gguf Q5_K_M 5 32 GB large, very low quality loss - recommended
Qwen1.5-110B-Chat-Q5_K_M-00003-of-00003.gguf Q5_K_M 5 14.8 GB large, very low quality loss - recommended

Quantized with llama.cpp b2824.