Instructions to use Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Baekpica/Solar-Open2-250B-Mixed-Quant-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 Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF
# Run inference directly in the terminal:
llama cli -hf Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF
# Run inference directly in the terminal:
llama cli -hf Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF

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 Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF
# Run inference directly in the terminal:
./llama-cli -hf Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF

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 Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF

Use Docker

docker model run hf.co/Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF

LM Studio
Jan

vLLM

How to use Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Baekpica/Solar-Open2-250B-Mixed-Quant-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": "Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF

Ollama
How to use Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF with Ollama:
```
ollama run hf.co/Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF
```
Unsloth Desktop

How to use Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF with Docker Model Runner:
```
docker model run hf.co/Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF
```

Lemonade

How to use Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF

Run and chat with the model

lemonade run user.Solar-Open2-250B-Mixed-Quant-GGUF-{{QUANT_TAG}}

List all available models

lemonade list

Hermes Agent

How to use Baekpica/Solar-Open2-250B-Mixed-Quant-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 Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF

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 Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF

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 "Baekpica/Solar-Open2-250B-Mixed-Quant-GGUF" \
  --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"

Solar-Open2-250B-Mixed-Quant-GGUF / compare-q8-v1-greedy.json

Baekpica

Add Q8 short comparison

8112484 verified 26 days ago

Raw

History Blame Contribute Delete

10.6 kB

	{
	"status": "ok",
	"errors": [],
	"scope": "structural and deterministic-output comparison; semantic quality remains a separately reported H100 sanity check",
	"reference": {
	"path": "/workspace/solar-open2-mixed-ds4/fixtures/reference/greedy-reference.json",
	"variant": "Q8_0"
	},
	"candidate": {
	"path": "/workspace/solar-open2-mixed-ds4/fixtures/reference/v1-greedy-reference.json",
	"variant": "MXQ-v1"
	},
	"summary": {
	"prompt_count": 32,
	"all_candidate_outputs_nonempty_and_token_ids_valid": true,
	"exact_sequence_count": 11,
	"first_token_match_count": 26,
	"mean_common_prefix_tokens": 20.375,
	"mean_position_match_rate": 0.66796875,
	"mean_sequence_match_ratio": 0.767578125
	},
	"comparisons": [
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	{
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	"candidate_stop": true,
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	"sequence_match_ratio": 0.65625,
	"candidate_stop": true,
	"candidate_stop_type": "limit"
	},
	{
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	"category": "ko_reasoning",
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	"sequence_match_ratio": 0.40625,
	"candidate_stop": true,
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	{
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	"candidate_stop_type": "limit"
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	{
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	"sequence_match_ratio": 0.4375,
	"candidate_stop": true,
	"candidate_stop_type": "limit"
	},
	{
	"id": "ko_reasoning_04",
	"category": "ko_reasoning",
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	"position_match_rate": 0.53125,
	"sequence_match_ratio": 0.53125,
	"candidate_stop": true,
	"candidate_stop_type": "limit"
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	{
	"id": "en_instruction_01",
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	"common_prefix_tokens": 32,
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	"sequence_match_ratio": 1.0,
	"candidate_stop": true,
	"candidate_stop_type": "limit"
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	{
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	"sequence_match_ratio": 0.96875,
	"candidate_stop": true,
	"candidate_stop_type": "limit"
	},
	{
	"id": "en_instruction_03",
	"category": "en_instruction",
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	"sequence_match_ratio": 1.0,
	"candidate_stop": true,
	"candidate_stop_type": "limit"
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	{
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	"sequence_match_ratio": 0.84375,
	"candidate_stop": true,
	"candidate_stop_type": "limit"
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	{
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	"candidate_stop_type": "limit"
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	}