Instructions to use King3Djbl/nexus-coder-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use King3Djbl/nexus-coder-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="King3Djbl/nexus-coder-GGUF",
	filename="nexus-coder-f16.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use King3Djbl/nexus-coder-GGUF 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 King3Djbl/nexus-coder-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf King3Djbl/nexus-coder-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf King3Djbl/nexus-coder-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf King3Djbl/nexus-coder-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf King3Djbl/nexus-coder-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf King3Djbl/nexus-coder-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf King3Djbl/nexus-coder-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf King3Djbl/nexus-coder-GGUF:Q4_K_M

Use Docker

docker model run hf.co/King3Djbl/nexus-coder-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use King3Djbl/nexus-coder-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "King3Djbl/nexus-coder-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "King3Djbl/nexus-coder-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/King3Djbl/nexus-coder-GGUF:Q4_K_M

Ollama
How to use King3Djbl/nexus-coder-GGUF with Ollama:
```
ollama run hf.co/King3Djbl/nexus-coder-GGUF:Q4_K_M
```

Unsloth Studio

How to use King3Djbl/nexus-coder-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for King3Djbl/nexus-coder-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for King3Djbl/nexus-coder-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for King3Djbl/nexus-coder-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use King3Djbl/nexus-coder-GGUF with Docker Model Runner:
```
docker model run hf.co/King3Djbl/nexus-coder-GGUF:Q4_K_M
```

Lemonade

How to use King3Djbl/nexus-coder-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull King3Djbl/nexus-coder-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.nexus-coder-GGUF-Q4_K_M

List all available models

lemonade list

NEXUS-Coder — GGUF Quantizations

GGUF quantized version of NEXUS-Coder.

Available Quantizations

File	Size
`IQ2_XXS.gguf`	488 MB
`Q2_K.gguf`	645 MB
`IQ3_XXS.gguf`	638 MB
`Q3_K_M.gguf`	786 MB
`Q4_0.gguf`	895 MB
`Q4_K_M.gguf`	940 MB
`IQ4_XS.gguf`	860 MB
`Q5_K_M.gguf`	1.0 GB
`Q6_K.gguf`	1.2 GB
`Q8_0.gguf`	1.5 GB
`F16.gguf`	2.9 GB

Usage

Ollama

ollama run hf.co/fableforge-ai/NEXUS-Coder

llama.cpp

./llama-cli -m nexus-coder-Q4_K_M.gguf --prompt "Write a Python function to merge two sorted lists" -n 512

Python (llama-cpp-python)

from llama_cpp import Llama
llm = Llama.from_pretrained(
    repo_id="King3Djbl/nexus-coder-GGUF",
    filename="nexus-coder-Q4_K_M.gguf",
)

License

Apache 2.0 — commercial use allowed.

Downloads last month: -

GGUF

Model size

2B params

Architecture

qwen2

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Model tree for King3Djbl/nexus-coder-GGUF

Base model

Qwen/Qwen2.5-1.5B

Finetuned

Qwen/Qwen2.5-1.5B-Instruct

Finetuned

fableforge-ai/NEXUS-Coder

Quantized

(1)

this model