second-state/Gemma-2b-it-GGUF

---

Gemma-2b-it

Original Model

google/gemma-2b-it

Run with LlamaEdge

• LlamaEdge version: v0.3.2

• Prompt template

  • Prompt type: gemma-instruct

  • Prompt string

    <start_of_turn>user
    {user_message}<end_of_turn>
    <start_of_turn>model
    {model_message}<end_of_turn>model
    

• Context size: 2048

• Run as LlamaEdge service

  wasmedge --dir .:. --nn-preload default:GGML:AUTO:gemma-2b-it-Q5_K_M.gguf llama-api-server.wasm -p gemma-instruct -c 4096
  

• Run as LlamaEdge command app

  wasmedge --dir .:. --nn-preload default:GGML:AUTO:gemma-2b-it-Q5_K_M.gguf llama-chat.wasm -p gemma-instruct -c 4096
  

Quantized GGUF Models

Name	Quant method	Bits	Size	Use case
gemma-2b-it-Q2_K.gguf	Q2_K	2	900 MB	smallest, significant quality loss - not recommended for most purposes
gemma-2b-it-Q3_K_L.gguf	Q3_K_L	3	1.26 GB	small, substantial quality loss
gemma-2b-it-Q3_K_M.gguf	Q3_K_M	3	1.18 GB	very small, high quality loss
gemma-2b-it-Q3_K_S.gguf	Q3_K_S	3	1.08 GB	very small, high quality loss
gemma-2b-it-Q4_0.gguf	Q4_0	4	1.42 GB	legacy; small, very high quality loss - prefer using Q3_K_M
gemma-2b-it-Q4_K_M.gguf	Q4_K_M	4	1.5 GB	medium, balanced quality - recommended
gemma-2b-it-Q4_K_S.gguf	Q4_K_S	4	1.42 GB	small, greater quality loss
gemma-2b-it-Q5_0.gguf	Q5_0	5	1.73 GB	legacy; medium, balanced quality - prefer using Q4_K_M
gemma-2b-it-Q5_K_M.gguf	Q5_K_M	5	1.77 GB	large, very low quality loss - recommended
gemma-2b-it-Q5_K_S.gguf	Q5_K_S	5	1.73 GB	large, low quality loss - recommended
gemma-2b-it-Q6_K.gguf	Q6_K	6	2.06 GB	very large, extremely low quality loss
gemma-2b-it-Q8_0.gguf	Q8_0	8	2.67 GB	very large, extremely low quality loss - not recommended

Quantized with llama.cpp b2230