Instructions to use andersoncda77/bella-tavola-sobremesa-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use andersoncda77/bella-tavola-sobremesa-v1 with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("andersoncda77/bella-tavola-sobremesa-v1", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
File size: 483 Bytes
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language: pt
tags:
- sklearn
- classification
- restaurant
- mlops
- fastapi
---
# bella-tavola-sobremesa-v1
Modelo de classificação binária treinado para prever **se o cliente vai pedir sobremesa** no restaurante Bella Tavola.
Desenvolvido como parte do curso de MLOps (Bloco 4).
## Como usar
```python
from huggingface_hub import hf_hub_download
import joblib
model = joblib.load(
hf_hub_download("andersoncda77/bella-tavola-sobremesa-v1", "model.pkl")
) |