Instructions to use l3cube-pune/gujarati-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/gujarati-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="l3cube-pune/gujarati-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/gujarati-bert") model = AutoModelForMaskedLM.from_pretrained("l3cube-pune/gujarati-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
Verified signature2ae3810
-
Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (53f1a9a21e6cc94de1f3ab4b2e088beb46eb19ff) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>d5c5c98
-
Update README.md
e5d95e0
-
Update README.md
b6417be
-
Update tokenizer_config.json
8a61d66
-
Update README.md
371ad94
-
Create README.md
ad6b7ac
-
Update model files
1e47b46 -
initial commit
cdd69eb