Instructions to use Kukedlc/Slopus-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kukedlc/Slopus-9B with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Kukedlc/Slopus-9B", dtype="auto") - llama-cpp-python
How to use Kukedlc/Slopus-9B with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Kukedlc/Slopus-9B", filename="Slopus-9B-Q2_K.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 Kukedlc/Slopus-9B 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 Kukedlc/Slopus-9B:Q4_K_M # Run inference directly in the terminal: llama cli -hf Kukedlc/Slopus-9B:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Kukedlc/Slopus-9B:Q4_K_M # Run inference directly in the terminal: llama cli -hf Kukedlc/Slopus-9B: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 Kukedlc/Slopus-9B:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Kukedlc/Slopus-9B: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 Kukedlc/Slopus-9B:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Kukedlc/Slopus-9B:Q4_K_M
Use Docker
docker model run hf.co/Kukedlc/Slopus-9B:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Kukedlc/Slopus-9B with Ollama:
ollama run hf.co/Kukedlc/Slopus-9B:Q4_K_M
- Unsloth Studio
How to use Kukedlc/Slopus-9B 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 Kukedlc/Slopus-9B 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 Kukedlc/Slopus-9B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Kukedlc/Slopus-9B to start chatting
- Pi
How to use Kukedlc/Slopus-9B with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Kukedlc/Slopus-9B: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": "Kukedlc/Slopus-9B:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Kukedlc/Slopus-9B with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Kukedlc/Slopus-9B: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 Kukedlc/Slopus-9B:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use Kukedlc/Slopus-9B with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Kukedlc/Slopus-9B:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "Kukedlc/Slopus-9B:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
- Docker Model Runner
How to use Kukedlc/Slopus-9B with Docker Model Runner:
docker model run hf.co/Kukedlc/Slopus-9B:Q4_K_M
- Lemonade
How to use Kukedlc/Slopus-9B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Kukedlc/Slopus-9B:Q4_K_M
Run and chat with the model
lemonade run user.Slopus-9B-Q4_K_M
List all available models
lemonade list
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| "add_prefix_space": false, | |
| "audio_bos_token": "<|audio_start|>", | |
| "audio_eos_token": "<|audio_end|>", | |
| "audio_token": "<|audio_pad|>", | |
| "backend": "tokenizers", | |
| "bos_token": null, | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|im_end|>", | |
| "errors": "replace", | |
| "image_token": "<|image_pad|>", | |
| "is_local": true, | |
| "model_max_length": 262144, | |
| "model_specific_special_tokens": { | |
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| "audio_eos_token": "<|audio_end|>", | |
| "audio_token": "<|audio_pad|>", | |
| "image_token": "<|image_pad|>", | |
| "video_token": "<|video_pad|>", | |
| "vision_bos_token": "<|vision_start|>", | |
| "vision_eos_token": "<|vision_end|>" | |
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| "pad_token": "<|endoftext|>", | |
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| "processor_class": "Qwen3VLProcessor", | |
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| }, | |
| "248064": { | |
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| "248069": { | |
| "content": "</think>", | |
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| "single_word": false, | |
| "lstrip": false, | |
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| }, | |
| "248073": { | |
| "content": "<tts_text_bos>", | |
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