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 flax_model.msgpack from oya163/NepBERT: direct link, hf CLI and curl.
- Browser
- Download file 334 MB
-
https://huggingface.co/oya163/NepBERT/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://oya163/NepBERT/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/oya163/NepBERT/resolve/main/flax_model.msgpack
334 MB
- Xet hash:
- eca2dfbe8a3616c85f8e2da0f4d106fe27892ee0887b70c31bd647fca6937ec3
- Size of remote file:
- 334 MB
- SHA256:
- 83bb66b5befed7379e6497960898352dcf64925acc67b12c0a1639005034ab03
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