Instructions to use kuppuluri/telugu_bertu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kuppuluri/telugu_bertu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="kuppuluri/telugu_bertu")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("kuppuluri/telugu_bertu") model = AutoModelForMaskedLM.from_pretrained("kuppuluri/telugu_bertu") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4812839371e98e0844b8442c2b6366e32a1cb076e864b385630781fd49eadf1b
- Size of remote file:
- 443 MB
- SHA256:
- cb5ec9eee99de2b2d9cb9d1ef6fff9c3e77c06108c7c946a186f17db0d66bfc1
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