Instructions to use crashx/telugu-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crashx/telugu-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="crashx/telugu-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("crashx/telugu-roberta-base") model = AutoModelForMaskedLM.from_pretrained("crashx/telugu-roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d4e8eecf6c6f7991363c51c7bcb1ce01f9dcabdbec03be98dae2f10c762ee03
- Size of remote file:
- 499 MB
- SHA256:
- fe966512d72d627347210aa8c4c6d27c1f5fa228f9f65cb607ec3052cdb25582
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