Instructions to use EQUES/jpharma-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EQUES/jpharma-bert-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("EQUES/jpharma-bert-base") model = AutoModelForPreTraining.from_pretrained("EQUES/jpharma-bert-base") - Notebooks
- Google Colab
- Kaggle
Improve model card: Add fill-mask pipeline tag, license, language, and domain tags
#1
by nielsr HF Staff - opened
This PR improves the model card by:
- Adding the
license: apache-2.0metadata. - Specifying the
pipeline_tag: fill-mask, enabling better discoverability at https://huggingface.co/models?pipeline_tag=fill-mask. - Including relevant
language: jaand additionaltagssuch asjapanese,pharmaceutical,bert, andcontinual-pretraining. - Adding a direct link to the paper and the GitHub repository at the top of the model card for better visibility.