---
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 |