Instructions to use HPLT/hplt_bert_base_ja with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HPLT/hplt_bert_base_ja with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HPLT/hplt_bert_base_ja", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("HPLT/hplt_bert_base_ja", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d20aa999058ba5b9ca65e95dd8552a78a7de5eefa8be5cc5e38f13a3fb9ca64
- Size of remote file:
- 525 MB
- SHA256:
- 3e21a9de348055be03680d628c5cc4abfdc5b857ba4d38441b6044f326cd7a8f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.