Yi-34B-Chat-GGUF / README.md
apepkuss79's picture
Update README.md
fd3a0d0 verified
|
raw
history blame
3.77 kB
metadata
base_model: 01-ai/Yi-34B-Chat
inference: false
license: other
license_link: LICENSE
license_name: yi-license
model_creator: 01-ai
model_name: Yi 34B Chat
model_type: yi
pipeline_tag: text-generation
quantized_by: Second State Inc.

Yi-34B-Chat-GGUF

Original Model

01-ai/Yi-34B-Chat

Run with LlamaEdge

  • LlamaEdge version: v0.2.14 and above

  • Prompt template

    • Prompt type: chatml

    • Prompt string

      <|im_start|>system
      {system_message}<|im_end|>
      <|im_start|>user
      {prompt}<|im_end|>
      <|im_start|>assistant
      
    • Reverse prompt: <|im_end|>

  • Context size: 7168

  • Run as LlamaEdge service

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Yi-34B-Chat-Q5_K_M.gguf llama-api-server.wasm -p chatml -r '<|im_end|>'
    
  • Run as LlamaEdge command app

    wasmedge --dir .:. --nn-preload default:GGML:AUTO:Yi-34B-Chat-Q5_K_M.gguf llama-chat.wasm -p chatml -r '<|im_end|>'
    

Quantized GGUF Models

Name Quant method Bits Size Use case
Yi-34B-Chat-Q2_K.gguf Q2_K 2 12.8 GB smallest, significant quality loss - not recommended for most purposes
Yi-34B-Chat-Q3_K_L.gguf Q3_K_L 3 18.1 GB small, substantial quality loss
Yi-34B-Chat-Q3_K_M.gguf Q3_K_M 3 16.7 GB very small, high quality loss
Yi-34B-Chat-Q3_K_S.gguf Q3_K_S 3 15.0 GB very small, high quality loss
Yi-34B-Chat-Q4_0.gguf Q4_0 4 19.5 GB legacy; small, very high quality loss - prefer using Q3_K_M
Yi-34B-Chat-Q4_K_M.gguf Q4_K_M 4 20.7 GB medium, balanced quality - recommended
Yi-34B-Chat-Q4_K_S.gguf Q4_K_S 4 19.6 GB small, greater quality loss
Yi-34B-Chat-Q5_0.gguf Q5_0 5 23.7 GB legacy; medium, balanced quality - prefer using Q4_K_M
Yi-34B-Chat-Q5_K_M.gguf Q5_K_M 5 24.3 GB large, very low quality loss - recommended
Yi-34B-Chat-Q5_K_S.gguf Q5_K_S 5 23.7 GB large, low quality loss - recommended
Yi-34B-Chat-Q6_K.gguf Q6_K 6 28.2 GB very large, extremely low quality loss
Yi-34B-Chat-Q8_0.gguf Q8_0 8 36.5 GB very large, extremely low quality loss - not recommended

Quantized with llama.cpp b2037