Instructions to use Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix",
	filename="FuseChat-Kunoichi-10.7B-F16.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix: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 Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix: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 Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix:Q4_K_M

Use Docker

docker model run hf.co/Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix:Q4_K_M

LM Studio
Jan
Ollama
How to use Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix with Ollama:
```
ollama run hf.co/Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix:Q4_K_M
```

Unsloth Studio

How to use Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix 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 Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix 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 Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix to start chatting

Docker Model Runner
How to use Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix with Docker Model Runner:
```
docker model run hf.co/Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix:Q4_K_M
```

Lemonade

How to use Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Lewdiculous/FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix:Q4_K_M

Run and chat with the model

lemonade run user.FuseChat-Kunoichi-10.7B-GGUF-IQ-Imatrix-Q4_K_M

List all available models

lemonade list

This repository hosts GGUF-IQ-Imatrix quantizations for Virt-io/FuseChat-Kunoichi-10.7B.

Uploaded:

    quantization_options = [
        "Q4_K_M", "Q4_K_S", "IQ4_XS", "Q5_K_M", 
        "Q5_K_S", "Q6_K", "Q8_0", "IQ3_M", "IQ3_S", "IQ3_XS", "IQ3_XXS"
    ]

Downloads last month: 103

GGUF

Model size

11B params

Architecture

llama

Hardware compatibility

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

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Collection

Various GGUF quantizations of small models. Models with a "checkmark" are personal favorites. An "orange arrow" means it's being uploaded. • 97 items • Updated Mar 2 • 72