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

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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

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

## Getting Started

```bash
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

1. **Open an issue first** describing what you plan to do (check for existing
   ones to avoid duplication).
2. **Fork the repo** and create a branch.
3. Make your changes, keeping them **small and focused**.
4. **Verify** your change locally before opening a PR.
5. 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.