Instructions to use mascIT/bert-tiny-ita-lemma-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mascIT/bert-tiny-ita-lemma-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mascIT/bert-tiny-ita-lemma-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mascIT/bert-tiny-ita-lemma-classification") model = AutoModelForSequenceClassification.from_pretrained("mascIT/bert-tiny-ita-lemma-classification") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:4f917cde20ed63f7fa506770ab9f2c44238efb697dcf18b9b40e2b3d2db77c7b
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size 12164628
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