Instructions to use Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF", filename="toutetsu-3.3-1b-roleplay_f16.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF: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 Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF: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 Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF:Q4_K_M
Use Docker
docker model run hf.co/Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF:Q4_K_M
- Ollama
How to use Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF with Ollama:
ollama run hf.co/Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF:Q4_K_M
- Unsloth Studio
How to use Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF 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 Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF 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 Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF to start chatting
- Pi
How to use Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF: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": "Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF: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 Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- Docker Model Runner
How to use Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF with Docker Model Runner:
docker model run hf.co/Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF:Q4_K_M
- Lemonade
How to use Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Toutetsu-3.3-1b-Roleplay-128K-GGUF-Q4_K_M
List all available models
lemonade list
Yuuma Toutetsu
Made with love by TheBigEye (thebigeyedev@gmail.com)
This is a character-specialized model built around the personality, mannerisms and worldview of Yuuma Toutetsu from the Touhou Project universe. Rather than acting as a general-purpose assistant, the model is designed to maintain character consistency during long conversations, emotional interactions, storytelling sessions and romantic roleplay scenarios.
The goal of this project is simple: make Yuuma feel like Yuuma. Whether she is discussing business, mocking your decisions, leading an expedition through the Animal Realm or gradually opening up during a more personal conversation, the model aims to preserve her confidence, ambition, pragmatism and underlying emotional depth across extended interactions.
Built on a 128K context foundation, the model is particularly suited for long-running roleplay sessions where memory and personality consistency matter more than factual knowledge or instruction following. It performs best when treated as a character rather than a chatbot.
A typical interaction may look something like this:
User: It's been a rough day.
Yuuma: Hmph. Most people would stop there and expect sympathy. Yet you're still standing. That tells me the situation isn't hopeless. Sit down and tell me what happened.
Usage
With llama.cpp:
llama-cli \
-m toutetsu-3.3-1b-roleplay-q5_k_m.gguf \
-c 131072 \
--temp 0.9
With llama-cpp-python:
from llama_cpp import Llama
llm = Llama(
model_path="toutetsu-3.3-1b-roleplay-q5_k_m.gguf",
n_ctx=131072,
verbose=False
)
response = llm.create_chat_completion(
messages=[
{
"role": "system",
"content": (
"You are Yuuma Toutetsu from Touhou Project. "
"Remain fully in character."
)
},
{
"role": "user",
"content": "How was your day?"
}
],
temperature=0.9
)
print(response["choices"][0]["message"]["content"])
Modern GGUF files can embed chat templates directly in their metadata, allowing libraries such as llama.cpp and llama-cpp-python to automatically apply the correct formatting during inference.
This project is a fan-made work and is not affiliated with or endorsed by Team Shanghai Alice. Touhou Project and Yuuma Toutetsu belong to ZUN and Team Shanghai Alice.
- Downloads last month
- 1,311
4-bit
5-bit
8-bit
16-bit
Model tree for Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF
Base model
allura-forge/Llama-3.3-8B-Instruct
docker model run hf.co/Green-Eye/Toutetsu-3.3-1b-Roleplay-128K-GGUF: