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
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README.md
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# Training
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- epochs:
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- lr: 1e-5
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- optim: AdamW
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- weight_decay: 1e-
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# Eval
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- perplexity:
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# Training
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- epochs: 250
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- lr: 1e-5
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- optim: AdamW
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- weight_decay: 1e-4
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# Eval
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- perplexity: 45 (it's a 12MB model, don't expect this to be ChatGPT anytime soon :)
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