Instructions to use llamaraspberryrabbit/Solar-Open2-250B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use llamaraspberryrabbit/Solar-Open2-250B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="llamaraspberryrabbit/Solar-Open2-250B-GGUF", filename="Solar-Open2-250B-Q4_K_M-00001-of-00004.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 llamaraspberryrabbit/Solar-Open2-250B-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 llamaraspberryrabbit/Solar-Open2-250B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf llamaraspberryrabbit/Solar-Open2-250B-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 llamaraspberryrabbit/Solar-Open2-250B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf llamaraspberryrabbit/Solar-Open2-250B-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 llamaraspberryrabbit/Solar-Open2-250B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf llamaraspberryrabbit/Solar-Open2-250B-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 llamaraspberryrabbit/Solar-Open2-250B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf llamaraspberryrabbit/Solar-Open2-250B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/llamaraspberryrabbit/Solar-Open2-250B-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use llamaraspberryrabbit/Solar-Open2-250B-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "llamaraspberryrabbit/Solar-Open2-250B-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": "llamaraspberryrabbit/Solar-Open2-250B-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/llamaraspberryrabbit/Solar-Open2-250B-GGUF:Q4_K_M
- Ollama
How to use llamaraspberryrabbit/Solar-Open2-250B-GGUF with Ollama:
ollama run hf.co/llamaraspberryrabbit/Solar-Open2-250B-GGUF:Q4_K_M
- Unsloth Studio
How to use llamaraspberryrabbit/Solar-Open2-250B-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 llamaraspberryrabbit/Solar-Open2-250B-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 llamaraspberryrabbit/Solar-Open2-250B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for llamaraspberryrabbit/Solar-Open2-250B-GGUF to start chatting
- Pi
How to use llamaraspberryrabbit/Solar-Open2-250B-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf llamaraspberryrabbit/Solar-Open2-250B-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": "llamaraspberryrabbit/Solar-Open2-250B-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use llamaraspberryrabbit/Solar-Open2-250B-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 llamaraspberryrabbit/Solar-Open2-250B-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 llamaraspberryrabbit/Solar-Open2-250B-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use llamaraspberryrabbit/Solar-Open2-250B-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf llamaraspberryrabbit/Solar-Open2-250B-GGUF: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 "llamaraspberryrabbit/Solar-Open2-250B-GGUF: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 llamaraspberryrabbit/Solar-Open2-250B-GGUF with Docker Model Runner:
docker model run hf.co/llamaraspberryrabbit/Solar-Open2-250B-GGUF:Q4_K_M
- Lemonade
How to use llamaraspberryrabbit/Solar-Open2-250B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull llamaraspberryrabbit/Solar-Open2-250B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Solar-Open2-250B-GGUF-Q4_K_M
List all available models
lemonade list
Solar-Open2-250B-GGUF
Built with Solar
Unofficial community GGUF quantizations of upstage/Solar-Open2-250B. Not affiliated with, sponsored by, or endorsed by Upstage. This is an independent derivative work.
Available quantizations
Q4_K_M(~141 GB) —Solar-Open2-250B-Q4_K_M-*-of-*.gguf. The 128-wide KDA gate projections (ssm_f_b/ssm_g_b) fall backq4_K→q5_0, as is normal for Kimi-family linear-attention models.Q8_0(~250 GB) —Solar-Open2-250B-Q8_0-*-of-*.gguf. Near-lossless; no fallbacks (Q8_0's 32-wide blocks quantize the 128-wide gates cleanly).
Both are split into <50 GB shards; point llama.cpp at the first shard of a set and it loads the rest automatically.
Modification notice: these files were modified from the original — converted to GGUF and quantized from the original bf16 weights.
⚠️ Requires a patched llama.cpp
Solar-Open2 is a hybrid MoE (KDA linear attention + gated GQA + DeepSeek-V3-style
MoE) and its architecture is not in upstream llama.cpp. To run these GGUFs you
must build llama.cpp from the fork that adds the solar-open2 architecture:
https://github.com/llamaraspberryrabbit/llama.cpp/tree/add-solar-open2
⚠️ This fork is AI-created and will not be upstreamed
That fork — the HF→GGUF converter, the C++ inference graph, the reasoning-parser patch, and these quantizations — was created by AI (Claude Opus 4.8). It has not been numerically validated against Upstage's reference implementation, and no pull request will be opened against upstream llama.cpp. Treat it as an experimental, community-grade artifact, and review the code yourself before relying on it — you are responsible for anything you run.
It has been verified to load and generate coherent, factually correct output
on a CUDA build, and reasoning is parsed into reasoning_content — but see the
caveat above.
Usage
# reasoning model — a repeat penalty is recommended
llama-cli -m Solar-Open2-250B-Q4_K_M-00001-of-000NN.gguf \
-ngl 99 -c 8192 --jinja --reasoning-format deepseek \
--repeat-penalty 1.2 -cnv
llama.cpp loads the shard set automatically when you point it at the first shard.
License
Built with Solar. Licensed under the Upstage Solar License (see the
LICENSE file in this repo, included per Section 4(e)). The original
Solar-Open2 model is © Upstage Co., Ltd. Per the license, this derivative's name
begins with "Solar" and displays "Built with Solar." Use of the "Solar" name does
not imply any endorsement by or official relationship with Upstage.
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upstage/Solar-Open2-250B