GGUF
Spanish
English
deepseek_v2
moderno-tech
nova
nova-coder
quantized
code-generation
local-ai
custom_code
conversational
Instructions to use ModernoTech/Nova-Coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use ModernoTech/Nova-Coder with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf ModernoTech/Nova-Coder:Q4_K_M # Run inference directly in the terminal: llama cli -hf ModernoTech/Nova-Coder:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ModernoTech/Nova-Coder:Q4_K_M # Run inference directly in the terminal: llama cli -hf ModernoTech/Nova-Coder:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf ModernoTech/Nova-Coder:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf ModernoTech/Nova-Coder:Q4_K_M
Use Docker
docker model run hf.co/ModernoTech/Nova-Coder:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use ModernoTech/Nova-Coder with Ollama:
ollama run hf.co/ModernoTech/Nova-Coder:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use ModernoTech/Nova-Coder with Docker Model Runner:
docker model run hf.co/ModernoTech/Nova-Coder:Q4_K_M
- Lemonade
How to use ModernoTech/Nova-Coder with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ModernoTech/Nova-Coder:Q4_K_M
Run and chat with the model
lemonade run user.Nova-Coder-Q4_K_M
List all available models
lemonade list
- Atomic Chat
File size: 5,008 Bytes
22c1157 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 | ---
base_model: deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct
inference: false
license: other
license_name: deepseek-license
license_link: LICENSE
model_creator: DeepSeek-ai
model_name: DeepSeek-Coder-V2-Lite-Instruct
model_type: deepseek
quantized_by: Second State Inc.
---
<!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://github.com/LlamaEdge/LlamaEdge/raw/dev/assets/logo.svg" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
<!-- header end -->
# DeepSeek-Coder-V2-Lite-Instruct-GGUF
## Original Model
[deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct](https://huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct)
## Run with LlamaEdge
- LlamaEdge version: [v0.12.3](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.12.3) and above
- Prompt template
- Prompt type: `deepseek-chat-2`
- Prompt string
```text
<|begin_of_sentence|>{system_message}
User: {user_message_1}
Assistant: {assistant_message_1}<|end_of_sentence|>User: {user_message_2}
Assistant:
```
- Context size: `128000`
- Run as LlamaEdge service
```bash
wasmedge --dir .:. \
--nn-preload default:GGML:AUTO:DeepSeek-Coder-V2-Lite-Instruct-Q5_K_M.gguf \
llama-api-server.wasm \
--prompt-template deepseek-chat-2 \
--ctx-size 128000 \
--model-name DeepSeek-Coder-V2-Lite-Instruct
```
- Run as LlamaEdge command app
```bash
wasmedge --dir .:. \
--nn-preload default:GGML:AUTO:DeepSeek-Coder-V2-Lite-Instruct-Q5_K_M.gguf \
llama-chat.wasm \
--prompt-template deepseek-chat-2 \
--ctx-size 128000
```
## Quantized GGUF Models
| Name | Quant method | Bits | Size | Use case |
| ---- | ---- | ---- | ---- | ----- |
| [DeepSeek-Coder-V2-Lite-Instruct-Q2_K.gguf](https://huggingface.co/second-state/DeepSeek-Coder-V2-Lite-Instruct-GGUF/blob/main/DeepSeek-Coder-V2-Lite-Instruct-Q2_K.gguf) | Q2_K | 2 | 6.43 GB| smallest, significant quality loss - not recommended for most purposes |
| [DeepSeek-Coder-V2-Lite-Instruct-Q3_K_L.gguf](https://huggingface.co/second-state/DeepSeek-Coder-V2-Lite-Instruct-GGUF/blob/main/DeepSeek-Coder-V2-Lite-Instruct-Q3_K_L.gguf) | Q3_K_L | 3 | 8.46 GB| small, substantial quality loss |
| [DeepSeek-Coder-V2-Lite-Instruct-Q3_K_M.gguf](https://huggingface.co/second-state/DeepSeek-Coder-V2-Lite-Instruct-GGUF/blob/main/DeepSeek-Coder-V2-Lite-Instruct-Q3_K_M.gguf) | Q3_K_M | 3 | 8.13 GB| very small, high quality loss |
| [DeepSeek-Coder-V2-Lite-Instruct-Q3_K_S.gguf](https://huggingface.co/second-state/DeepSeek-Coder-V2-Lite-Instruct-GGUF/blob/main/DeepSeek-Coder-V2-Lite-Instruct-Q3_K_S.gguf) | Q3_K_S | 3 | 7.49 GB| very small, high quality loss |
| [DeepSeek-Coder-V2-Lite-Instruct-Q4_0.gguf](https://huggingface.co/second-state/DeepSeek-Coder-V2-Lite-Instruct-GGUF/blob/main/DeepSeek-Coder-V2-Lite-Instruct-Q4_0.gguf) | Q4_0 | 4 | 8.91 GB| legacy; small, very high quality loss - prefer using Q3_K_M |
| [DeepSeek-Coder-V2-Lite-Instruct-Q4_K_M.gguf](https://huggingface.co/second-state/DeepSeek-Coder-V2-Lite-Instruct-GGUF/blob/main/DeepSeek-Coder-V2-Lite-Instruct-Q4_K_M.gguf) | Q4_K_M | 4 | 10.4 GB| medium, balanced quality - recommended |
| [DeepSeek-Coder-V2-Lite-Instruct-Q4_K_S.gguf](https://huggingface.co/second-state/DeepSeek-Coder-V2-Lite-Instruct-GGUF/blob/main/DeepSeek-Coder-V2-Lite-Instruct-Q4_K_S.gguf) | Q4_K_S | 4 | 9.53 GB| small, greater quality loss |
| [DeepSeek-Coder-V2-Lite-Instruct-Q5_0.gguf](https://huggingface.co/second-state/DeepSeek-Coder-V2-Lite-Instruct-GGUF/blob/main/DeepSeek-Coder-V2-Lite-Instruct-Q5_0.gguf) | Q5_0 | 5 | 10.8 GB| legacy; medium, balanced quality - prefer using Q4_K_M |
| [DeepSeek-Coder-V2-Lite-Instruct-Q5_K_M.gguf](https://huggingface.co/second-state/DeepSeek-Coder-V2-Lite-Instruct-GGUF/blob/main/DeepSeek-Coder-V2-Lite-Instruct-Q5_K_M.gguf) | Q5_K_M | 5 | 11.9 GB| large, very low quality loss - recommended |
| [DeepSeek-Coder-V2-Lite-Instruct-Q5_K_S.gguf](https://huggingface.co/second-state/DeepSeek-Coder-V2-Lite-Instruct-GGUF/blob/main/DeepSeek-Coder-V2-Lite-Instruct-Q5_K_S.gguf) | Q5_K_S | 5 | 11.1 GB| large, low quality loss - recommended |
| [DeepSeek-Coder-V2-Lite-Instruct-Q6_K.gguf](https://huggingface.co/second-state/DeepSeek-Coder-V2-Lite-Instruct-GGUF/blob/main/DeepSeek-Coder-V2-Lite-Instruct-Q6_K.gguf) | Q6_K | 6 | 14.1 GB| very large, extremely low quality loss |
| [DeepSeek-Coder-V2-Lite-Instruct-Q8_0.gguf](https://huggingface.co/second-state/DeepSeek-Coder-V2-Lite-Instruct-GGUF/blob/main/DeepSeek-Coder-V2-Lite-Instruct-Q8_0.gguf) | Q8_0 | 8 | 16.7 GB| very large, extremely low quality loss - not recommended |
| [DeepSeek-Coder-V2-Lite-Instruct-f16.gguf](https://huggingface.co/second-state/DeepSeek-Coder-V2-Lite-Instruct-GGUF/blob/main/DeepSeek-Coder-V2-Lite-Instruct-f16.gguf) | f16 | 16 | 31.4 GB| |
*Quatized with llama.cpp b3212*
|