--- base_model: deepseek-ai/deepseek-coder-6.7b-instruct inference: false license: other license_link: LICENSE license_name: deepseek model_creator: DeepSeek model_name: Deepseek Coder 6.7B Instruct model_type: deepseek quantized_by: Second State Inc. ---

# Deepseek-Coder-6.7B-Instruct-GGUF ## Original Model [deepseek-ai/deepseek-coder-6.7b-instruct](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instruct) ## Run with LlamaEdge - LlamaEdge version: [v0.2.8](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.2.8) and above - Prompt template - Prompt type: `deepseek-coder` - Prompt string ```text {system} \### Instruction: {question_1} \### Response: {answer_1} <|EOT|> \### Instruction: {question_2} \### Response: ``` Note that the `\` character is used to escape the `###` in the prompt string. Remove it in the practical use. - Context size: `4096` - Run as LlamaEdge service ```bash wasmedge --dir .:. --nn-preload default:GGML:AUTO:deepseek-coder-6.7b-instruct-Q5_K_M.gguf llama-api-server.wasm -p deepseek-coder ``` - Run as LlamaEdge command app ```bash wasmedge --dir .:. --nn-preload default:GGML:AUTO:deepseek-coder-6.7b-instruct-Q5_K_M.gguf llama-chat.wasm -p deepseek-coder ``` ## Quantized GGUF Models | Name | Quant method | Bits | Size | Use case | | ---- | ---- | ---- | ---- | ----- | | [deepseek-coder-6.7b-instruct-Q2_K.gguf](https://huggingface.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF/blob/main/deepseek-coder-6.7b-instruct-Q2_K.gguf) | Q2_K | 2 | 2.53 GB| smallest, significant quality loss - not recommended for most purposes | | [deepseek-coder-6.7b-instruct-Q3_K_L.gguf](https://huggingface.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF/blob/main/deepseek-coder-6.7b-instruct-Q3_K_L.gguf) | Q3_K_L | 3 | 3.6 GB| small, substantial quality loss | | [deepseek-coder-6.7b-instruct-Q3_K_M.gguf](https://huggingface.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF/blob/main/deepseek-coder-6.7b-instruct-Q3_K_M.gguf) | Q3_K_M | 3 | 3.3 GB| very small, high quality loss | | [deepseek-coder-6.7b-instruct-Q3_K_S.gguf](https://huggingface.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF/blob/main/deepseek-coder-6.7b-instruct-Q3_K_S.gguf) | Q3_K_S | 3 | 2.95 GB| very small, high quality loss | | [deepseek-coder-6.7b-instruct-Q4_0.gguf](https://huggingface.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF/blob/main/deepseek-coder-6.7b-instruct-Q4_0.gguf) | Q4_0 | 4 | 3.83 GB| legacy; small, very high quality loss - prefer using Q3_K_M | | [deepseek-coder-6.7b-instruct-Q4_K_M.gguf](https://huggingface.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF/blob/main/deepseek-coder-6.7b-instruct-Q4_K_M.gguf) | Q4_K_M | 4 | 4.08 GB| medium, balanced quality - recommended | | [deepseek-coder-6.7b-instruct-Q4_K_S.gguf](https://huggingface.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF/blob/main/deepseek-coder-6.7b-instruct-Q4_K_S.gguf) | Q4_K_S | 4 | 3.86 GB| small, greater quality loss | | [deepseek-coder-6.7b-instruct-Q5_0.gguf](https://huggingface.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF/blob/main/deepseek-coder-6.7b-instruct-Q5_0.gguf) | Q5_0 | 5 | 4.65 GB| legacy; medium, balanced quality - prefer using Q4_K_M | | [deepseek-coder-6.7b-instruct-Q5_K_M.gguf](https://huggingface.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF/blob/main/deepseek-coder-6.7b-instruct-Q5_K_M.gguf) | Q5_K_M | 5 | 4.79 GB| large, very low quality loss - recommended | | [deepseek-coder-6.7b-instruct-Q5_K_S.gguf](https://huggingface.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF/blob/main/deepseek-coder-6.7b-instruct-Q5_K_S.gguf) | Q5_K_S | 5 | 4.65 GB| large, low quality loss - recommended | | [deepseek-coder-6.7b-instruct-Q6_K.gguf](https://huggingface.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF/blob/main/deepseek-coder-6.7b-instruct-Q6_K.gguf) | Q6_K | 6 | 5.53 GB| very large, extremely low quality loss | | [deepseek-coder-6.7b-instruct-Q8_0.gguf](https://huggingface.co/second-state/Deepseek-Coder-6.7B-Instruct-GGUF/blob/main/deepseek-coder-6.7b-instruct-Q8_0.gguf) | Q8_0 | 8 | 7.16 GB| very large, extremely low quality loss - not recommended |