Text Generation
MLX
Safetensors
English
Italian
qwen3
finance
financial-reasoning
investment-research
risk-management
portfolio-analysis
market-regime
financial-sentiment
explainable-ai
conversational
4-bit precision
Instructions to use Italianhype/Blum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Italianhype/Blum 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("Italianhype/Blum") 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 Italianhype/Blum with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "Italianhype/Blum"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "Italianhype/Blum" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Italianhype/Blum 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 "Italianhype/Blum"
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 Italianhype/Blum
Run Hermes
hermes
- OpenClaw new
How to use Italianhype/Blum with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "Italianhype/Blum"
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 "Italianhype/Blum" \ --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"
- MLX LM
How to use Italianhype/Blum with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "Italianhype/Blum"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "Italianhype/Blum" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Italianhype/Blum", "messages": [ {"role": "user", "content": "Hello"} ] }'
| [build-system] | |
| requires = ["hatchling>=1.27"] | |
| build-backend = "hatchling.build" | |
| [project] | |
| name = "blum-finance" | |
| version = "0.1.0" | |
| description = "Structured local inference and opt-in contribution tools for BLUM Finance." | |
| requires-python = ">=3.11" | |
| license = { text = "Apache-2.0" } | |
| dependencies = [ | |
| "pydantic>=2.10,<3", | |
| ] | |
| [project.optional-dependencies] | |
| inference = [ | |
| "accelerate>=1.2", | |
| "torch>=2.4", | |
| "transformers>=4.51", | |
| ] | |
| mlx = [ | |
| "mlx-lm>=0.31,<0.32", | |
| ] | |
| hub = [ | |
| "huggingface-hub>=0.30", | |
| ] | |
| release = [ | |
| "huggingface-hub>=0.30", | |
| "jinja2>=3.1", | |
| ] | |
| test = [ | |
| "pytest>=8.3", | |
| ] | |
| [project.scripts] | |
| blum-contribute = "blum_finance.contributions:main" | |
| [tool.hatch.build.targets.wheel] | |
| packages = ["blum_finance"] | |