Instructions to use iarfmoose/roberta-small-bulgarian with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iarfmoose/roberta-small-bulgarian with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="iarfmoose/roberta-small-bulgarian")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("iarfmoose/roberta-small-bulgarian") model = AutoModelForMaskedLM.from_pretrained("iarfmoose/roberta-small-bulgarian") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 04dfc0cc0ca126e6a2ce3643c6bde5a0abe4a1755256335174c8a9d3a391e562
- Size of remote file:
- 334 MB
- SHA256:
- dd41e7e88920623a88a9076c34c3ee6ac135bfc6378da11c067898e2a942efc1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.