Instructions to use Hemg/mask-langauge-modeling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hemg/mask-langauge-modeling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Hemg/mask-langauge-modeling")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Hemg/mask-langauge-modeling") model = AutoModelForMaskedLM.from_pretrained("Hemg/mask-langauge-modeling") - Notebooks
- Google Colab
- Kaggle
Ctrl+K