Instructions to use DhimanBose/Bangla_Masked_Language_Model3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DhimanBose/Bangla_Masked_Language_Model3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="DhimanBose/Bangla_Masked_Language_Model3")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("DhimanBose/Bangla_Masked_Language_Model3") model = AutoModelForMaskedLM.from_pretrained("DhimanBose/Bangla_Masked_Language_Model3") - Notebooks
- Google Colab
- Kaggle
Commit History
Upload tokenizer_config.json edc1df8 verified
Upload ElectraForMaskedLM ab0dd19
Upload ElectraForMaskedLM ae0e247
Upload ElectraForMaskedLM adbb893
Upload ElectraForMaskedLM 61a5a67
Upload ElectraForMaskedLM 266d899
Upload ElectraForMaskedLM 8b8282c
Upload ElectraForMaskedLM d5f830f
initial commit 0ce404d
Dhiman Kumer Bose commited on