Fill-Mask
Transformers
Safetensors
Turkish
English
modernbert
masked-lm
long-context
turkish
code
mathematics
Instructions to use boun-tabilab/TabiBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boun-tabilab/TabiBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="boun-tabilab/TabiBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("boun-tabilab/TabiBERT") model = AutoModelForMaskedLM.from_pretrained("boun-tabilab/TabiBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c1d41268de74b609aad93fb9439a9610a4f6be20ce030aeeb1c7e4435e39e14
- Size of remote file:
- 598 MB
- SHA256:
- b9e047c0d91ce3a295e6c44c6c5d1fcd9aaff5428ce9796491e8d55a2c568b5c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.