Instructions to use kofdai/refactorium-dual-deepseek-r1-7b-plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use kofdai/refactorium-dual-deepseek-r1-7b-plus 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 kofdai/refactorium-dual-deepseek-r1-7b-plus:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf kofdai/refactorium-dual-deepseek-r1-7b-plus:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf kofdai/refactorium-dual-deepseek-r1-7b-plus:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf kofdai/refactorium-dual-deepseek-r1-7b-plus: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 kofdai/refactorium-dual-deepseek-r1-7b-plus:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf kofdai/refactorium-dual-deepseek-r1-7b-plus: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 kofdai/refactorium-dual-deepseek-r1-7b-plus:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf kofdai/refactorium-dual-deepseek-r1-7b-plus:Q4_K_M

Use Docker

docker model run hf.co/kofdai/refactorium-dual-deepseek-r1-7b-plus:Q4_K_M

LM Studio
Jan

vLLM

How to use kofdai/refactorium-dual-deepseek-r1-7b-plus with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "kofdai/refactorium-dual-deepseek-r1-7b-plus"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "kofdai/refactorium-dual-deepseek-r1-7b-plus",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/kofdai/refactorium-dual-deepseek-r1-7b-plus:Q4_K_M

Ollama
How to use kofdai/refactorium-dual-deepseek-r1-7b-plus with Ollama:
```
ollama run hf.co/kofdai/refactorium-dual-deepseek-r1-7b-plus:Q4_K_M
```

Unsloth Studio

How to use kofdai/refactorium-dual-deepseek-r1-7b-plus 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 kofdai/refactorium-dual-deepseek-r1-7b-plus 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 kofdai/refactorium-dual-deepseek-r1-7b-plus to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for kofdai/refactorium-dual-deepseek-r1-7b-plus to start chatting

Docker Model Runner
How to use kofdai/refactorium-dual-deepseek-r1-7b-plus with Docker Model Runner:
```
docker model run hf.co/kofdai/refactorium-dual-deepseek-r1-7b-plus:Q4_K_M
```

Lemonade

How to use kofdai/refactorium-dual-deepseek-r1-7b-plus with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull kofdai/refactorium-dual-deepseek-r1-7b-plus:Q4_K_M

Run and chat with the model

lemonade run user.refactorium-dual-deepseek-r1-7b-plus-Q4_K_M

List all available models

lemonade list

Atomic Chat

refactorium-dual-deepseek-r1-7b-plus

File size: 1,425 Bytes

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# Refactorium 環境変数テンプレート
# このファイルを .env にコピーして、環境に応じた値を設定してください

# ===== データベース設定 =====
DB_HOST=localhost
DB_PORT=5432
DB_USER=refactorium
DB_PASSWORD=your_secure_password_here
DB_NAME=refactorium
DB_POOL_SIZE=10
DB_MAX_OVERFLOW=20

# ===== Redis 設定 =====
REDIS_HOST=localhost
REDIS_PORT=6379
REDIS_DB=0
REDIS_PASSWORD=
REDIS_TIMEOUT=5

# ===== Refactorium 設定 =====
REFACTORIUM_ENV=development
REFACTORIUM_DEBUG=true

# ===== API 設定 =====
API_HOST=0.0.0.0
API_PORT=8000
API_WORKERS=4
API_RELOAD=true

# ===== ロギング設定 =====
LOG_LEVEL=debug
LOG_FILE=refactorium.log
LOG_MAX_BYTES=10485760
LOG_BACKUP_COUNT=5

# ===== セキュリティ設定 =====
API_KEY_SECRET=your_api_key_secret_here
JWT_SECRET=your_jwt_secret_here
JWT_EXPIRATION_HOURS=24

# ===== リソース制限 =====
MAX_MEMORY_MB=4000
MAX_CPU_PERCENT=80
REQUEST_TIMEOUT_SECONDS=60
MAX_CONCURRENT_REQUESTS=100

# ===== モデル設定 =====
MODEL_CACHE_SIZE=3
MODEL_MAX_MEMORY_MB=8000
DEFAULT_MODEL=main_model
SHADOW_MODEL=shadow_model

# ===== メモリ・ストレージ設定 =====
CHROMA_PATH=./data/chroma
SQLITE_PATH=./data/refactorium.db
MEMORY_TTL_DAYS=90

# ===== MCP 設定 =====
MCP_ENABLED=true
MCP_TIMEOUT_SECONDS=30
MCP_MAX_EVENTS_PER_SECOND=100

# ===== 開発者向け =====
ENABLE_PROFILING=false
ENABLE_MOCK_MODELS=false
SEED=42