Instructions to use HPLT/hplt_bert_base_be with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HPLT/hplt_bert_base_be with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HPLT/hplt_bert_base_be", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("HPLT/hplt_bert_base_be", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b80c2a03435fbd45c0a0b1722b279f38ab3c0cbb1443946ace3c66aa787ec5df
- Size of remote file:
- 525 MB
- SHA256:
- d589ccb744da93b53a477eeaa83bb68c7159d6694e6ae470566eb495ac5c60e2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.