Instructions to use mascIT/bert-tiny-ita with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mascIT/bert-tiny-ita with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mascIT/bert-tiny-ita")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mascIT/bert-tiny-ita") model = AutoModelForMaskedLM.from_pretrained("mascIT/bert-tiny-ita") - Notebooks
- Google Colab
- Kaggle
bert-tiny-ita is an italian foundational model (based on bert-tiny) pretrained from scratch on 20k italian Wikipedia articles and on a wide collection of italian words and dictionary definitions. It uses 512 context window size.
The project is still a work in progress, new versions will come with time.
Use it as a foundational model to be finetuned for specific italian tasks.
Training
- epochs: 250
- lr: 1e-5
- optim: AdamW
- weight_decay: 1e-4
Eval
- perplexity: 45 (it's a 12MB model!)
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