Instructions to use HPLT/hplt_bert_base_it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HPLT/hplt_bert_base_it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HPLT/hplt_bert_base_it", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("HPLT/hplt_bert_base_it", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1bab8ef4505e92294271327685f68db8952f6c6a0cff046bb5d9461fccc14624
- Size of remote file:
- 525 MB
- SHA256:
- 2ff6416dbc2f734e63ca0140abf88c9676b068ac691b466dfdf35d8b7cb1c6ad
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.