Instructions to use HPLT/hplt_bert_base_mt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HPLT/hplt_bert_base_mt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HPLT/hplt_bert_base_mt", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("HPLT/hplt_bert_base_mt", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 53cebb8bc3fe22d0eecb25242fe16987b69aad9774e5beb3dfa1c2f69e067700
- Size of remote file:
- 475 MB
- SHA256:
- a180fa2885ca53cdd5a3335b6d98bdddc295f2e846293f255a28ccf16b62766a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.