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
| 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 | |