Instructions to use Temur/qartvelian-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Temur/qartvelian-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Temur/qartvelian-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Temur/qartvelian-roberta-base") model = AutoModelForMaskedLM.from_pretrained("Temur/qartvelian-roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b0a229991dfa00ed6fc60c024cbc19a0788d0a42796649d3f4539d9f9487868
- Size of remote file:
- 499 MB
- SHA256:
- 1335233c4b6bd20669c25ee8b486135ca5ff65f3aadcf16c655b719d54ddf8d5
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