Text Generation
Safetensors
GGUF
Rust
English
Vietnamese
dioxus
accessibility
wcag
fine-tuned
raft
code
server-functions
qwen3
family-hub
scoped-css
syncstore
conversational
Instructions to use rockypod/neotoi-coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use rockypod/neotoi-coder with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="rockypod/neotoi-coder", filename="neotoi-coder-v1-q4_k_m_final.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use rockypod/neotoi-coder with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf rockypod/neotoi-coder:Q4_K_M # Run inference directly in the terminal: llama-cli -hf rockypod/neotoi-coder:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf rockypod/neotoi-coder:Q4_K_M # Run inference directly in the terminal: llama-cli -hf rockypod/neotoi-coder: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 rockypod/neotoi-coder:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf rockypod/neotoi-coder: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 rockypod/neotoi-coder:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf rockypod/neotoi-coder:Q4_K_M
Use Docker
docker model run hf.co/rockypod/neotoi-coder:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use rockypod/neotoi-coder with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "rockypod/neotoi-coder" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rockypod/neotoi-coder", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/rockypod/neotoi-coder:Q4_K_M
- Ollama
How to use rockypod/neotoi-coder with Ollama:
ollama run hf.co/rockypod/neotoi-coder:Q4_K_M
- Unsloth Studio new
How to use rockypod/neotoi-coder 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 rockypod/neotoi-coder 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 rockypod/neotoi-coder to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for rockypod/neotoi-coder to start chatting
- Pi new
How to use rockypod/neotoi-coder with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf rockypod/neotoi-coder:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "rockypod/neotoi-coder:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use rockypod/neotoi-coder with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf rockypod/neotoi-coder:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default rockypod/neotoi-coder:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use rockypod/neotoi-coder with Docker Model Runner:
docker model run hf.co/rockypod/neotoi-coder:Q4_K_M
- Lemonade
How to use rockypod/neotoi-coder with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull rockypod/neotoi-coder:Q4_K_M
Run and chat with the model
lemonade run user.neotoi-coder-Q4_K_M
List all available models
lemonade list
| Neotoi Coder | |
| Copyright 2026 Kevin Miller, Jr. | |
| This product includes derivative work based on the following models | |
| released by Alibaba Cloud / Qwen Team under the Apache License, | |
| Version 2.0: | |
| - Qwen3-Coder-14B (base for the 14B variant of Neotoi Coder) | |
| - Qwen3-Coder-Next 80B (teacher model for synthetic training data) | |
| The Apache 2.0 license text for these upstream models is available | |
| in the LICENSE-APACHE file in this repository. | |
| The Neotoi Coder fine-tuning work, dataset, and trained adapter weights | |
| are licensed separately under the Neotoi Coder Community License v1.0 | |
| (see LICENSE). | |
| Modifications: LoRA adapters trained on the proprietary Neotoi Coder | |
| RAFT dataset (Dioxus 0.7 / Rust / Tailwind v4 / WCAG 2.2 AAA), then | |
| merged into the base model and quantized to GGUF. | |