Instructions to use swadesh7/bert_telugu_23 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use swadesh7/bert_telugu_23 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="swadesh7/bert_telugu_23")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("swadesh7/bert_telugu_23") model = AutoModelForMaskedLM.from_pretrained("swadesh7/bert_telugu_23", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from swadesh7/bert_telugu_23: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/swadesh7/bert_telugu_23/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://swadesh7/bert_telugu_23/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/swadesh7/bert_telugu_23/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- d756843680d125d648184e4b0356256545c198d2f0488082a9e84a19bfeb330b
- Size of remote file:
- 443 MB
- SHA256:
- 8e0098f58191f179ecf504a9cfd835834149b55b525f7491b84f3510545afc17
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