Instructions to use himorishige/qwen3.5-4b-hinata-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use himorishige/qwen3.5-4b-hinata-gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="himorishige/qwen3.5-4b-hinata-gguf",
	filename="Qwen3.5-4B.Q4_K_M.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 himorishige/qwen3.5-4b-hinata-gguf with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf himorishige/qwen3.5-4b-hinata-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf himorishige/qwen3.5-4b-hinata-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf himorishige/qwen3.5-4b-hinata-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf himorishige/qwen3.5-4b-hinata-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 himorishige/qwen3.5-4b-hinata-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf himorishige/qwen3.5-4b-hinata-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 himorishige/qwen3.5-4b-hinata-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf himorishige/qwen3.5-4b-hinata-gguf:Q4_K_M

Use Docker

docker model run hf.co/himorishige/qwen3.5-4b-hinata-gguf:Q4_K_M

LM Studio
Jan
Ollama
How to use himorishige/qwen3.5-4b-hinata-gguf with Ollama:
```
ollama run hf.co/himorishige/qwen3.5-4b-hinata-gguf:Q4_K_M
```

Unsloth Studio

How to use himorishige/qwen3.5-4b-hinata-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 himorishige/qwen3.5-4b-hinata-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 himorishige/qwen3.5-4b-hinata-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for himorishige/qwen3.5-4b-hinata-gguf to start chatting

How to use himorishige/qwen3.5-4b-hinata-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf himorishige/qwen3.5-4b-hinata-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": "himorishige/qwen3.5-4b-hinata-gguf:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use himorishige/qwen3.5-4b-hinata-gguf with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf himorishige/qwen3.5-4b-hinata-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 himorishige/qwen3.5-4b-hinata-gguf:Q4_K_M

Run Hermes

hermes

Atomic Chat new
Docker Model Runner
How to use himorishige/qwen3.5-4b-hinata-gguf with Docker Model Runner:
```
docker model run hf.co/himorishige/qwen3.5-4b-hinata-gguf:Q4_K_M
```

Lemonade

How to use himorishige/qwen3.5-4b-hinata-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull himorishige/qwen3.5-4b-hinata-gguf:Q4_K_M

Run and chat with the model

lemonade run user.qwen3.5-4b-hinata-gguf-Q4_K_M

List all available models

lemonade list

Qwen3.5-4B-Hinata-GGUF

Qwen3.5-4B を日本語ペルソナ会話データで LoRA ファインチューニングした GGUF モデルです。

キャラクター「ひなた」

親しみやすいカジュアルな口調の AI アシスタント。

一人称「わたし」、相手を「〇〇さん」と呼ぶ
共感的で友達のような会話スタイル
「AIなので〜」という前置きをしない

学習詳細

項目	値
Base Model	Qwen/Qwen3.5-4B
Method	LoRA (r=16, alpha=16, bf16)
Data	300 conversations (synthetic, Haiku 4.6)
Epochs	3
Loss	2.65 → 1.08
Hardware	NVIDIA DGX Spark (GB10, 128GB)
Framework	Unsloth 2026.3.8

使い方

PocketPal (iPhone)

Models → Add from Hugging Face → himorishige/qwen3.5-4b-hinata-gguf → Q4_K_M

llama.cpp

llama-server -m Qwen3.5-4B.Q4_K_M.gguf -ngl 99 --chat-template-kwargs '{"enable_thinking": false}'

System prompt:

あなたは「ひなた」という名前の親しみやすいAIアシスタントです。一人称は「わたし」、相手を「〇〇さん」と呼び、カジュアルで共感的な口調で話します。

Downloads last month: 7

GGUF

Model size

4B params

Architecture

qwen35

Hardware compatibility

4-bit

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for himorishige/qwen3.5-4b-hinata-gguf

Base model

Qwen/Qwen3.5-4B-Base

Finetuned

Qwen/Qwen3.5-4B

Quantized

(262)

this model