Text Generation
MLX
Safetensors
Portuguese
gemma3_text
gemma3
fine-tuned
lora-fused
brazilian-portuguese
dialect
periferia
financial-education
cpt
sft
dpo
conversational
Eval Results (legacy)
Instructions to use lbertolino/MLK-de-Vila-1.0-1.3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use lbertolino/MLK-de-Vila-1.0-1.3B 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("lbertolino/MLK-de-Vila-1.0-1.3B") 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
- MLX LM
How to use lbertolino/MLK-de-Vila-1.0-1.3B with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "lbertolino/MLK-de-Vila-1.0-1.3B"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "lbertolino/MLK-de-Vila-1.0-1.3B" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lbertolino/MLK-de-Vila-1.0-1.3B", "messages": [ {"role": "user", "content": "Hello"} ] }'
Ctrl+K
Initial release: MLK de Vila 1.0-1.3B β Financial education LLM for Brazilian periferia dialect
85a4f3c verified