Instructions to use vinhood/chefberto-italian-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vinhood/chefberto-italian-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="vinhood/chefberto-italian-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("vinhood/chefberto-italian-cased") model = AutoModelForMaskedLM.from_pretrained("vinhood/chefberto-italian-cased") - Notebooks
- Google Colab
- Kaggle
ChefBERTo 👨🍳
chefberto-italian-cased is a BERT model obtained by MLM adaptive-tuning bert-base-italian-xxl-cased on Italian cooking recipes, approximately 50k sentences (2.6M words).
Author: Cristiano De Nobili (@denocris on Twitter, LinkedIn) for VINHOOD.
Perplexity
Test set: 9k sentences about food.
| Model | Perplexity |
|---|---|
| chefberto-italian-cased | 1.84 |
| bert-base-italian-xxl-cased | 2.85 |
Usage
from transformers import AutoModel, AutoTokenizer
model_name = "vinhood/chefberto-italian-cased"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModel.from_pretrained(model_name)
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