--- license: gemma library_name: transformers pipeline_tag: text-generation base_model: shenzhi-wang/Gemma-2-9B-Chinese-Chat inference: false model_creator: shenzhi-wang model_name: Gemma-2-9B-Chinese-Chat quantized_by: Second State Inc. language: - en - zh ---

# Gemma-2-9B-Chinese-Chat-GGUF ## Original Model [shenzhi-wang/Gemma-2-9B-Chinese-Chat](https://huggingface.co/shenzhi-wang/Gemma-2-9B-Chinese-Chat) ## Run with LlamaEdge - LlamaEdge version: [v0.12.1](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.12.1) and above - Prompt template - Prompt type: `gemma-instruct` - Prompt string ```text user {user_message} model {model_message}model ``` - Context size: `8192` - Run as LlamaEdge service ```bash wasmedge --dir .:. --nn-preload default:GGML:AUTO:Gemma-2-9B-Chinese-Chat-Q5_K_M.gguf \ llama-api-server.wasm \ --prompt-template gemma-instruct \ --ctx-size 8192 \ --model-name gemma-2-9b ``` - Run as LlamaEdge command app ```bash wasmedge --dir .:. \ --nn-preload default:GGML:AUTO:Gemma-2-9B-Chinese-Chat-Q5_K_M.gguf \ llama-chat.wasm \ --prompt-template gemma-instruct \ --ctx-size 8192 ``` ## Quantized GGUF Models | Name | Quant method | Bits | Size | Use case | | ---- | ---- | ---- | ---- | ----- | | [Gemma-2-9B-Chinese-Chat-Q2_K.gguf](https://huggingface.co/second-state/Gemma-2-9B-Chinese-Chat-GGUF/blob/main/Gemma-2-9B-Chinese-Chat-Q2_K.gguf) | Q2_K | 2 | 3.81 GB| smallest, significant quality loss - not recommended for most purposes | | [Gemma-2-9B-Chinese-Chat-Q3_K_L.gguf](https://huggingface.co/second-state/Gemma-2-9B-Chinese-Chat-GGUF/blob/main/Gemma-2-9B-Chinese-Chat-Q3_K_L.gguf) | Q3_K_L | 3 | 5.13 GB| small, substantial quality loss | | [Gemma-2-9B-Chinese-Chat-Q3_K_M.gguf](https://huggingface.co/second-state/Gemma-2-9B-Chinese-Chat-GGUF/blob/main/Gemma-2-9B-Chinese-Chat-Q3_K_M.gguf) | Q3_K_M | 3 | 4.76 GB| very small, high quality loss | | [Gemma-2-9B-Chinese-Chat-Q3_K_S.gguf](https://huggingface.co/second-state/Gemma-2-9B-Chinese-Chat-GGUF/blob/main/Gemma-2-9B-Chinese-Chat-Q3_K_S.gguf) | Q3_K_S | 3 | 4.34 GB| very small, high quality loss | | [Gemma-2-9B-Chinese-Chat-Q4_0.gguf](https://huggingface.co/second-state/Gemma-2-9B-Chinese-Chat-GGUF/blob/main/Gemma-2-9B-Chinese-Chat-Q4_0.gguf) | Q4_0 | 4 | 5.44 GB| legacy; small, very high quality loss - prefer using Q3_K_M | | [Gemma-2-9B-Chinese-Chat-Q4_K_M.gguf](https://huggingface.co/second-state/Gemma-2-9B-Chinese-Chat-GGUF/blob/main/Gemma-2-9B-Chinese-Chat-Q4_K_M.gguf) | Q4_K_M | 4 | 5.76 GB| medium, balanced quality - recommended | | [Gemma-2-9B-Chinese-Chat-Q4_K_S.gguf](https://huggingface.co/second-state/Gemma-2-9B-Chinese-Chat-GGUF/blob/main/Gemma-2-9B-Chinese-Chat-Q4_K_S.gguf) | Q4_K_S | 4 | 5.48 GB| small, greater quality loss | | [Gemma-2-9B-Chinese-Chat-Q5_0.gguf](https://huggingface.co/second-state/Gemma-2-9B-Chinese-Chat-GGUF/blob/main/Gemma-2-9B-Chinese-Chat-Q5_0.gguf) | Q5_0 | 5 | 6.48 GB| legacy; medium, balanced quality - prefer using Q4_K_M | | [Gemma-2-9B-Chinese-Chat-Q5_K_M.gguf](https://huggingface.co/second-state/Gemma-2-9B-Chinese-Chat-GGUF/blob/main/Gemma-2-9B-Chinese-Chat-Q5_K_M.gguf) | Q5_K_M | 5 | 6.65 GB| large, very low quality loss - recommended | | [Gemma-2-9B-Chinese-Chat-Q5_K_S.gguf](https://huggingface.co/second-state/Gemma-2-9B-Chinese-Chat-GGUF/blob/main/Gemma-2-9B-Chinese-Chat-Q5_K_S.gguf) | Q5_K_S | 5 | 6.48 GB| large, low quality loss - recommended | | [Gemma-2-9B-Chinese-Chat-Q6_K.gguf](https://huggingface.co/second-state/Gemma-2-9B-Chinese-Chat-GGUF/blob/main/Gemma-2-9B-Chinese-Chat-Q6_K.gguf) | Q6_K | 6 | 7.59 GB| very large, extremely low quality loss | | [Gemma-2-9B-Chinese-Chat-Q8_0.gguf](https://huggingface.co/second-state/Gemma-2-9B-Chinese-Chat-GGUF/blob/main/Gemma-2-9B-Chinese-Chat-Q8_0.gguf) | Q8_0 | 8 | 9.83 GB| very large, extremely low quality loss - not recommended | | [Gemma-2-9B-Chinese-Chat-f16.gguf](https://huggingface.co/second-state/Gemma-2-9B-Chinese-Chat-GGUF/blob/main/Gemma-2-9B-Chinese-Chat-f16.gguf) | f16 | 16 | 18.5 GB| | *Quantized with llama.cpp b3259*