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:
- 6b9cc6a9cda7d169b9f5698054e6670854532c25c7af36aeebbb08451078f431
- Size of remote file:
- 670 MB
- SHA256:
- 77011395c8ef14f0b9a66d52a3022fd19f99e52668380642e54abe7d51a4bd63
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