Instructions to use Andrija/SRoBERTa-L with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Andrija/SRoBERTa-L with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Andrija/SRoBERTa-L")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Andrija/SRoBERTa-L") model = AutoModelForMaskedLM.from_pretrained("Andrija/SRoBERTa-L") - Notebooks
- Google Colab
- Kaggle
Roberta model called SRoBERTa trained on WOL dataset (OSCAR + Leipzig + srWac) for Serbian language. Attention heads distilled 6, batch size 64, group size 64, epochs 2, test split 0.05(~1mil groups)
4e75a39 - Xet hash:
- 47158ed370f527f49b7ca3a37ecb2da610defab8f024c761457aacdf0ca94cda
- Size of remote file:
- 322 MB
- SHA256:
- e7d6251e1f8cc0a6dc6b494e952a1413792f71ce3e78a211a26d883c6cbaa0c5
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