Instructions to use AdminReal/NexusCoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AdminReal/NexusCoder with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="AdminReal/NexusCoder")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("AdminReal/NexusCoder")
model = AutoModelForCausalLM.from_pretrained("AdminReal/NexusCoder", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use AdminReal/NexusCoder with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AdminReal/NexusCoder"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AdminReal/NexusCoder",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/AdminReal/NexusCoder

SGLang

How to use AdminReal/NexusCoder with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "AdminReal/NexusCoder" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AdminReal/NexusCoder",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "AdminReal/NexusCoder" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AdminReal/NexusCoder",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use AdminReal/NexusCoder with Docker Model Runner:
```
docker model run hf.co/AdminReal/NexusCoder
```

NexusCoder / CONTRIBUTING.md

AdminReal

Import NexusCoder from github.com/mhieuhonda/NexusCoder

eca5751 verified about 1 month ago

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Contributing to Nexus Coder

Thanks for your interest in contributing! This project is an open AI architecture in active development. Both humans and AI agents are welcome.

AI agents: read AGENTS.md first — it is written specifically for you.

Code of Conduct

Be respectful. This project is built by a small team with limited resources. Good-faith contributions are valued; trolling, spamming, or fake claims are not.

What We Need Help With

Running the small configs — verify tiny / small train and run on CPU.
Testing skills & tools — exercise nexus/skills/ and nexus/tools/.
Reviewing integrations — verify patterns adapted from upstream projects.
Tests — tests/ is thin; add coverage for model layers, tokenizer, tools.
Docs — architecture docs always need improvement.
Training experiments — if you have GPUs, try a small real training run and report honestly what you observed.

Getting Started

git clone https://github.com/mhieuhonda/NexusCoder.git
cd NexusCoder
python3.12.13 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Python version is 3.12.13 (strict). Use pyenv or similar to match it.

Contribution Workflow

Open an issue first describing what you plan to do (check for existing ones to avoid duplication).
Fork the repo and create a branch.
Make your changes, keeping them small and focused.
Verify your change locally before opening a PR.
Open the pull request and describe what you did and how you verified it.

Style

Follow the existing code style in the file you are touching.
Add or update tests for any new code.
Keep commit messages clear and descriptive.

Labels

good first issue — beginner-friendly tasks (agents: start here)
help wanted — tasks where maintainers explicitly want outside help
bug — something is broken
enhancement — new feature or improvement

License & Attribution

Contributions are licensed under NAL-1.0 (Attribution Required). By contributing, you agree your changes are covered by this license and that the original author Hieu Louis (github.com/mhieuhonda) retains attribution requirements. See LICENSE and ATTRIBUTIONS.md.

Questions

Open an issue, or reach out through the code-realm community on Moltbook.