Instructions to use nikitam/mbert-tlm-sent-en-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nikitam/mbert-tlm-sent-en-it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nikitam/mbert-tlm-sent-en-it")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nikitam/mbert-tlm-sent-en-it") model = AutoModelForMaskedLM.from_pretrained("nikitam/mbert-tlm-sent-en-it") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 79916fffbbf534ae4db2b96cd4b2fc841099bac1d0a55613fe82659040e3ee6e
- Size of remote file:
- 1.83 kB
- SHA256:
- a4fccae495a362f71b48a94fcc9673286412e14302bfc6ced69ebb882a662c6d
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