--- base_model: google/datagemma-rig-27b-it inference: false license: gemma library_name: transformers pipeline_tag: text-generation model_creator: Google model_name: datagemma-rig-27b-it quantized_by: Second State Inc. tags: - conversational ---

# Datagemma-rig-27b-it-GGUF ## Original Model [google/datagemma-rig-27b-it](https://huggingface.co/google/datagemma-rig-27b-it) ## Run with LlamaEdge - LlamaEdge version: [v0.14.3](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.14.3) 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:datagemma-rig-27b-it-Q5_K_M.gguf \ llama-api-server.wasm \ --prompt-template gemma-instruct \ --ctx-size 8192 \ --model-name gemma-2-27b ``` - Run as LlamaEdge command app ```bash wasmedge --dir .:. \ --nn-preload default:GGML:AUTO:datagemma-rig-27b-it-Q5_K_M.gguf \ llama-chat.wasm \ --prompt-template gemma-instruct \ --ctx-size 8192 ``` ## Quantized GGUF Models | Name | Quant method | Bits | Size | Use case | | ---- | ---- | ---- | ---- | ----- | | [datagemma-rig-27b-it-Q2_K.gguf](https://huggingface.co/second-state/datagemma-rig-27b-it-GGUF/blob/main/datagemma-rig-27b-it-Q2_K.gguf) | Q2_K | 2 | 10.4 GB| smallest, significant quality loss - not recommended for most purposes | | [datagemma-rig-27b-it-Q3_K_L.gguf](https://huggingface.co/second-state/datagemma-rig-27b-it-GGUF/blob/main/datagemma-rig-27b-it-Q3_K_L.gguf) | Q3_K_L | 3 | 14.5 GB| small, substantial quality loss | | [datagemma-rig-27b-it-Q3_K_M.gguf](https://huggingface.co/second-state/datagemma-rig-27b-it-GGUF/blob/main/datagemma-rig-27b-it-Q3_K_M.gguf) | Q3_K_M | 3 | 13.4 GB| very small, high quality loss | | [datagemma-rig-27b-it-Q3_K_S.gguf](https://huggingface.co/second-state/datagemma-rig-27b-it-GGUF/blob/main/datagemma-rig-27b-it-Q3_K_S.gguf) | Q3_K_S | 3 | 12.2 GB| very small, high quality loss | | [datagemma-rig-27b-it-Q4_0.gguf](https://huggingface.co/second-state/datagemma-rig-27b-it-GGUF/blob/main/datagemma-rig-27b-it-Q4_0.gguf) | Q4_0 | 4 | 15.6 GB| legacy; small, very high quality loss - prefer using Q3_K_M | | [datagemma-rig-27b-it-Q4_K_M.gguf](https://huggingface.co/second-state/datagemma-rig-27b-it-GGUF/blob/main/datagemma-rig-27b-it-Q4_K_M.gguf) | Q4_K_M | 4 | 16.6 GB| medium, balanced quality - recommended | | [datagemma-rig-27b-it-Q4_K_S.gguf](https://huggingface.co/second-state/datagemma-rig-27b-it-GGUF/blob/main/datagemma-rig-27b-it-Q4_K_S.gguf) | Q4_K_S | 4 | 15.7 GB| small, greater quality loss | | [datagemma-rig-27b-it-Q5_0.gguf](https://huggingface.co/second-state/datagemma-rig-27b-it-GGUF/blob/main/datagemma-rig-27b-it-Q5_0.gguf) | Q5_0 | 5 | 18.9 GB| legacy; medium, balanced quality - prefer using Q4_K_M | | [datagemma-rig-27b-it-Q5_K_M.gguf](https://huggingface.co/second-state/datagemma-rig-27b-it-GGUF/blob/main/datagemma-rig-27b-it-Q5_K_M.gguf) | Q5_K_M | 5 | 19.4 GB| large, very low quality loss - recommended | | [datagemma-rig-27b-it-Q5_K_S.gguf](https://huggingface.co/second-state/datagemma-rig-27b-it-GGUF/blob/main/datagemma-rig-27b-it-Q5_K_S.gguf) | Q5_K_S | 5 | 18.9 GB| large, low quality loss - recommended | | [datagemma-rig-27b-it-Q6_K.gguf](https://huggingface.co/second-state/datagemma-rig-27b-it-GGUF/blob/main/datagemma-rig-27b-it-Q6_K.gguf) | Q6_K | 6 | 22.3 GB| very large, extremely low quality loss | | [datagemma-rig-27b-it-Q8_0.gguf](https://huggingface.co/second-state/datagemma-rig-27b-it-GGUF/blob/main/datagemma-rig-27b-it-Q8_0.gguf) | Q8_0 | 8 | 28.9 GB| very large, extremely low quality loss - not recommended | | [datagemma-rig-27b-it-f16-00001-of-00002.gguf](https://huggingface.co/second-state/datagemma-rig-27b-it-GGUF/blob/main/datagemma-rig-27b-it-f16-00001-of-00002.gguf) | f16 | 16 | 29.9 GB| | | [datagemma-rig-27b-it-f16-00002-of-00002.gguf](https://huggingface.co/second-state/datagemma-rig-27b-it-GGUF/blob/main/datagemma-rig-27b-it-f16-00002-of-00002.gguf) | f16 | 16 | 24.6 GB| | *Quantized with llama.cpp b3664*