Instructions to use RecursiveSI/flint-int4-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 RecursiveSI/flint-int4-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 RecursiveSI/flint-int4-gguf:Q4_1
# Run inference directly in the terminal:
llama cli -hf RecursiveSI/flint-int4-gguf:Q4_1

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf RecursiveSI/flint-int4-gguf:Q4_1
# Run inference directly in the terminal:
llama cli -hf RecursiveSI/flint-int4-gguf:Q4_1

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 RecursiveSI/flint-int4-gguf:Q4_1
# Run inference directly in the terminal:
./llama-cli -hf RecursiveSI/flint-int4-gguf:Q4_1

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 RecursiveSI/flint-int4-gguf:Q4_1
# Run inference directly in the terminal:
./build/bin/llama-cli -hf RecursiveSI/flint-int4-gguf:Q4_1

Use Docker

docker model run hf.co/RecursiveSI/flint-int4-gguf:Q4_1

LM Studio
Jan

vLLM

How to use RecursiveSI/flint-int4-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "RecursiveSI/flint-int4-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": "RecursiveSI/flint-int4-gguf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/RecursiveSI/flint-int4-gguf:Q4_1

Ollama
How to use RecursiveSI/flint-int4-gguf with Ollama:
```
ollama run hf.co/RecursiveSI/flint-int4-gguf:Q4_1
```
Unsloth Desktop

How to use RecursiveSI/flint-int4-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf RecursiveSI/flint-int4-gguf:Q4_1

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": "RecursiveSI/flint-int4-gguf:Q4_1"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use RecursiveSI/flint-int4-gguf with Docker Model Runner:
```
docker model run hf.co/RecursiveSI/flint-int4-gguf:Q4_1
```

Lemonade

How to use RecursiveSI/flint-int4-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull RecursiveSI/flint-int4-gguf:Q4_1

Run and chat with the model

lemonade run user.flint-int4-gguf-Q4_1

List all available models

lemonade list

Hermes Agent

How to use RecursiveSI/flint-int4-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 RecursiveSI/flint-int4-gguf:Q4_1

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 RecursiveSI/flint-int4-gguf:Q4_1

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use RecursiveSI/flint-int4-gguf with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf RecursiveSI/flint-int4-gguf:Q4_1

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 "RecursiveSI/flint-int4-gguf:Q4_1" \
  --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"

flint-int4-gguf

File size: 779 Bytes

4be1201

{
  "$schema": "https://opencode.ai/config.json",
  "model": "flint-local/flint",
  "small_model": "flint-local/flint",
  "provider": {
    "flint-local": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Flint (local)",
      "options": {
        "baseURL": "http://127.0.0.1:8080/v1",
        "apiKey": "local"
      },
      "models": {
        "flint": {
          "name": "Flint",
          "reasoning": true,
          "interleaved": {
            "field": "reasoning_content"
          },
          "limit": {
            "context": 262144,
            "output": 65536
          }
        }
      }
    }
  },
  "agent": {
    "build": {
      "temperature": 1.0,
      "top_p": 0.95
    },
    "plan": {
      "temperature": 1.0,
      "top_p": 0.95
    }
  }
}