Instructions to use subbareddyoota/roberta_ltrc_telugu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use subbareddyoota/roberta_ltrc_telugu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="subbareddyoota/roberta_ltrc_telugu")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("subbareddyoota/roberta_ltrc_telugu") model = AutoModelForMaskedLM.from_pretrained("subbareddyoota/roberta_ltrc_telugu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a7c04f0250091c631a602b5141843c3992ac6ded3d614e48364a7af970ac8997
- Size of remote file:
- 962 MB
- SHA256:
- a56d246a71b5553ead495e9baf815eb076b435cb4ef5cd9103ae5fbdf474bab9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.