Instructions to use subbareddyoota/bert_ltrc_telugu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use subbareddyoota/bert_ltrc_telugu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="subbareddyoota/bert_ltrc_telugu")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("subbareddyoota/bert_ltrc_telugu") model = AutoModelForMaskedLM.from_pretrained("subbareddyoota/bert_ltrc_telugu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from subbareddyoota/bert_ltrc_telugu: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/subbareddyoota/bert_ltrc_telugu/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://subbareddyoota/bert_ltrc_telugu/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/subbareddyoota/bert_ltrc_telugu/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- 7b15ec925aa41b37d30bbbb9408be1106772dbcf442cac324c0fa23f3f0fa6bd
- Size of remote file:
- 433 MB
- SHA256:
- e02a23c71c352a16b58eb4454aa15e07ba3f4a14fe84d034357454afc457336e
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