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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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language:
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This model (based on [bert-tiny](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2)) has been trained from scratch on 20k italian Wikipedia articles and on a wide collection of italian words and dictionary definitions.
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# Eval
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- perplexity: 50 (it's a 12MB model, don't expect this to be ChatGPT anytime soon :)
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pipeline_tag: sentence-similarity
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This model (based on [bert-tiny](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2)) has been trained from scratch on 20k italian Wikipedia articles and on a wide collection of italian words and dictionary definitions.
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# Eval
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- perplexity: 50 (it's a 12MB model, don't expect this to be ChatGPT anytime soon :)
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