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rockypod
/
neotoi-coder

Text Generation
Safetensors
GGUF
Rust
English
Vietnamese
dioxus
accessibility
wcag
fine-tuned
raft
code
server-functions
qwen3
family-hub
scoped-css
syncstore
conversational
Model card Files Files and versions
xet
Community
1

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
78.3 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 36 commits
rockypod's picture
rockypod
docs: add 8B + 4B v3.2 scorecards, mark all three variants published
32d0ca9 verified 4 days ago
  • mlx-v3.1
    Add files using upload-large-folder tool 28 days ago
  • mlx-v3.2
    Add v3.2 15B MLX 4-bit (7.7 GB, 2 shards) 4 days ago
  • mlx-v3
    v3.0.0: add MLX 4-bit weights (4.5 bpw, 7.8 GiB) about 1 month ago
  • mlx
    Add files using upload-large-folder tool about 1 month ago
  • .gitattributes
    2.1 kB
    Add v3.2 15B MLX 4-bit (7.7 GB, 2 shards) 4 days ago
  • LICENSE
    1.34 kB
    Upload LICENSE with huggingface_hub about 2 months ago
  • LICENSE-APACHE
    11.4 kB
    Add Apache 2.0 attribution for upstream Qwen base model and teacher 23 days ago
  • NOTICE
    786 Bytes
    Add Apache 2.0 attribution for upstream Qwen base model and teacher 23 days ago
  • README.md
    11 kB
    docs: add 8B + 4B v3.2 scorecards, mark all three variants published 4 days ago
  • neotoi-coder-v1-q4_k_m_final.gguf
    9 GB
    xet
    fix: replace broken tokenizer with correct Qwen3 vocab arrays about 2 months ago
  • neotoi-coder-v2.0-q4_k_m.gguf
    9 GB
    xet
    Add Neotoi Coder v2.0 Q4_K_M GGUF — 135.5/140 (96.8%) about 1 month ago
  • neotoi-coder-v3-q4_k_m_patched.gguf
    9 GB
    xet
    v3.0.0: add GGUF Q4_K_M (8.4 GiB, patched for thinking template) about 1 month ago
  • neotoi-coder-v3.1-q4_k_m.gguf
    9 GB
    xet
    Upload neotoi-coder-v3.1-q4_k_m.gguf with huggingface_hub 29 days ago
  • neotoi-coder-v3.2-q4_k_m_patched.gguf
    9 GB
    xet
    Add v3.2 15B Q4_K_M GGUF (95.12% on 114Q exam) 4 days ago