Instructions to use mor40/BulBERT-chitanka-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mor40/BulBERT-chitanka-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mor40/BulBERT-chitanka-model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mor40/BulBERT-chitanka-model") model = AutoModelForMaskedLM.from_pretrained("mor40/BulBERT-chitanka-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 67daf80f609f682aafd7faf8ea587740ba189dddd54c6a07bae4b0e7140627bc
- Size of remote file:
- 329 MB
- SHA256:
- 2747c07e6c4141379ab9968dbd85b8f2135b9a419ae25b7a9f6a6df42ab2c01b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.