Instructions to use RecursiveSI/flint-int4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use RecursiveSI/flint-int4 with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("RecursiveSI/flint-int4") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use RecursiveSI/flint-int4 with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "RecursiveSI/flint-int4"
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "RecursiveSI/flint-int4" } ] } } }Run Pi
# Start Pi in your project directory: pi
- MLX LM
How to use RecursiveSI/flint-int4 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "RecursiveSI/flint-int4"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "RecursiveSI/flint-int4" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "RecursiveSI/flint-int4", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use RecursiveSI/flint-int4 with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "RecursiveSI/flint-int4"
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
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use RecursiveSI/flint-int4 with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "RecursiveSI/flint-int4"
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" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Download flint-int4.json from RecursiveSI/flint-int4: direct link, hf CLI and curl.
- Browser
- Download file 1.21 kB
-
https://huggingface.co/RecursiveSI/flint-int4/resolve/main/flint-int4.json
- Command line
-
hf download hf://RecursiveSI/flint-int4/flint-int4.json
-
curl -L -o flint-int4.json https://huggingface.co/RecursiveSI/flint-int4/resolve/main/flint-int4.json
1.21 kB
| { | |
| "model_id": "flint-int4", | |
| "weight_format": "mlx-affine-int4", | |
| "kv_format": "bf16", | |
| "max_context": 262144, | |
| "checkpoint_files": { | |
| "chat_template.jinja": "7940f4ffa3275c36caa4a582f845aaad79da11018b3961e8fbcad6ae29733466", | |
| "config.json": "80f577a984db1bd40dfff88457b611d4c13e807704a945616be27f28809eed21", | |
| "generation_config.json": "a499c71895e008abd572558a5ad5904feaed92cf2a3b6e2cb0e9cabf03b96ed3", | |
| "model-00000.safetensors": "1a362742a0136c95ed751e2c56d83e63d4ed9ac674984b23b368f105d16cfe7a", | |
| "model-00001.safetensors": "12979140fa019042ff5cdec4c0237cc87db13b56428ce7fe093dd9d33893ea32", | |
| "model-00002.safetensors": "01805c6b882fdec008b0184ec68e7516102205b521e63ca5126f9d52b9aed87b", | |
| "model-00003.safetensors": "9380ed032d90e0ff566d49672faf292f354b3b0e7320820c150eeed8c75e9d42", | |
| "model-00004.safetensors": "c1ba12d2c2a80feb5e554554a01cfde2b71c2638e27fc0ee597b4121399eff99", | |
| "special_tokens_map.json": "be37b302338dda189bc70bfbe902d8faebeb5986d60c1342713439eefc4ca182", | |
| "tokenizer.json": "a263cce0b7e2b03f7ee07ce809783ef4b47f160c3f268a4ea1524f638da45b68", | |
| "tokenizer_config.json": "159ac88217e90ffd0a4a294726048bb302829e82e1958dc85bb203aa79138fbf" | |
| } | |
| } | |