Text Generation
Transformers
Safetensors
Portuguese
English
qwen3
conversational
text-generation-inference
Instructions to use prefeitura-rio/Rio-3.0-Open-Mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prefeitura-rio/Rio-3.0-Open-Mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="prefeitura-rio/Rio-3.0-Open-Mini") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("prefeitura-rio/Rio-3.0-Open-Mini") model = AutoModelForCausalLM.from_pretrained("prefeitura-rio/Rio-3.0-Open-Mini") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use prefeitura-rio/Rio-3.0-Open-Mini with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "prefeitura-rio/Rio-3.0-Open-Mini" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "prefeitura-rio/Rio-3.0-Open-Mini", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/prefeitura-rio/Rio-3.0-Open-Mini
- SGLang
How to use prefeitura-rio/Rio-3.0-Open-Mini with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "prefeitura-rio/Rio-3.0-Open-Mini" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "prefeitura-rio/Rio-3.0-Open-Mini", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "prefeitura-rio/Rio-3.0-Open-Mini" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "prefeitura-rio/Rio-3.0-Open-Mini", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use prefeitura-rio/Rio-3.0-Open-Mini with Docker Model Runner:
docker model run hf.co/prefeitura-rio/Rio-3.0-Open-Mini
Thanks
#2
by baldurian3 - opened
Hi, thanks for making this opensource. I am very happy to see more countries entering the race. Blessings to Rio ๐ง๐ท from India ๐ฎ๐ณ !!!
Also, gguf when???
Hi, thanks!
We have no plans to release official ggufs, however mradermacher already packaged some. I recommend using those: https://huggingface.co/mradermacher/Rio-3.0-Open-Mini-GGUF