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
metadata
license: mit
datasets:
- mor40/chitanka_raw_document
language:
- bg
metrics:
- perplexity
library_name: transformers
pipeline_tag: fill-mask
Model Card for Model ID
A LLM trained from scratch on bulgarian data. The model and the model's tokenizer are trained from scratch on bulgarian data from the chitanka dataset.
Metrics
Perprelixty - 6.75