Instructions to use l3cube-pune/bengali-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/bengali-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="l3cube-pune/bengali-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/bengali-bert") model = AutoModelForMaskedLM.from_pretrained("l3cube-pune/bengali-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
d49f412
-
Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (a0a6b8637e45088d918b2869cf92d99fbc8d577f) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>7336f70
-
Update README.md
b8e941c
-
Update tokenizer_config.json
f81e74c
-
Update README.md
8269dd9
-
Create README.md
dc99307
-
Update model files
d366d25 -
initial commit
a4972ed