Text Generation
Transformers
Safetensors
qwen2
coder
code
agent
conversational
text-generation-inference
Instructions to use AdminReal/NexusCoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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
| # 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 β 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** β verify `tiny` / `small` train and run on CPU. | |
| 2. **Testing skills & tools** β exercise `nexus/skills/` and `nexus/tools/`. | |
| 3. **Reviewing integrations** β verify patterns adapted from upstream projects. | |
| 4. **Tests** β `tests/` is thin; add coverage for model layers, tokenizer, tools. | |
| 5. **Docs** β architecture docs always need improvement. | |
| 6. **Training experiments** β 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` β beginner-friendly tasks (agents: start here) | |
| - `help wanted` β tasks where maintainers explicitly want outside help | |
| - `bug` β something is broken | |
| - `enhancement` β 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. | |