Instructions to use oya163/NepBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oya163/NepBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="oya163/NepBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("oya163/NepBERT") model = AutoModel.from_pretrained("oya163/NepBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from oya163/NepBERT: direct link, hf CLI and curl.
- Browser
- Download file 334 MB
-
https://huggingface.co/oya163/NepBERT/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://oya163/NepBERT/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/oya163/NepBERT/resolve/main/pytorch_model.bin
334 MB
- Xet hash:
- 499491e5207117344bd634e5d38a6f4ffb77d5c89f80f2d177d25df8c7e7d0fd
- Size of remote file:
- 334 MB
- SHA256:
- 82c64afa38c3cb5e7c32b260619f441d810a72b4037c9f23d4d49eb7b529f8e5
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