Text Generation
Transformers
Safetensors
Portuguese
gpt2
portuguese
brazilian-portuguese
conversational-ai
feminine
educational
text-generation-inference
Instructions to use naotodev/mateo1-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use naotodev/mateo1-mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="naotodev/mateo1-mini")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("naotodev/mateo1-mini") model = AutoModelForCausalLM.from_pretrained("naotodev/mateo1-mini", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use naotodev/mateo1-mini with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "naotodev/mateo1-mini" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "naotodev/mateo1-mini", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/naotodev/mateo1-mini
- SGLang
How to use naotodev/mateo1-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 "naotodev/mateo1-mini" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "naotodev/mateo1-mini", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "naotodev/mateo1-mini" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "naotodev/mateo1-mini", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use naotodev/mateo1-mini with Docker Model Runner:
docker model run hf.co/naotodev/mateo1-mini
Mateo-1 Mini
Modelo leve de IA conversacional com personalidade feminina. Treinado para ser carinhoso, paciente e acolhedora. Ideal para quem prefere uma assistente com tom mais suave e amigável.
Personality
Feminina - carinhosa e acolhedora
How to Use
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
# Load base model
base_model = AutoModelForCausalLM.from_pretrained("distilgpt2")
tokenizer = AutoTokenizer.from_pretrained("distilgpt2")
# Load LoRA adapter
model = PeftModel.from_pretrained(base_model, "mateo1-mini")
# Generate response
prompt = "<|system|>Modelo leve de IA conversacional com personalidade <|user|>Ola! <|assistant|>"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=150, temperature=0.7)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
Training Details
- Base Model: distilgpt2
- Method: LoRA (Low-Rank Adaptation)
- Language: Portuguese (Brazilian)
- Framework: PyTorch + Transformers + PEFT
Training
- Epochs: 5
- Final Loss: 9.1647
- Training Examples: ~825 exemplos de conversação e conhecimento geral em português brasileiro
Intended Use
This model is designed for conversational AI applications in Brazilian Portuguese. It can be used for:
- Educational assistance
- General conversation
- Knowledge questions
- Learning support
Limitations
- Small model size may limit complex reasoning
- Responses are in Brazilian Portuguese only
- May generate inaccurate information - always verify important facts
- Not suitable for critical applications without human oversight
Citation
@misc{mateo-core-mateo1-mini,
title={Mateo Core: Mateo-1 Mini},
author={Intelliski AI},
year={2026},
url={https://huggingface.co/intelliski/mateo1-mini}
}
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Model tree for naotodev/mateo1-mini
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distilbert/distilgpt2