Instructions to use nhrony/bert-bnsp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nhrony/bert-bnsp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nhrony/bert-bnsp")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nhrony/bert-bnsp") model = AutoModelForMaskedLM.from_pretrained("nhrony/bert-bnsp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nhrony/bert-bnsp: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/nhrony/bert-bnsp/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nhrony/bert-bnsp/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nhrony/bert-bnsp/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 2ae1feb04dd974ce326a6dbf185a809403a15de0b95c0a39f4288ab9bfd1f1d7
- Size of remote file:
- 268 MB
- SHA256:
- 5abe48abef18a362fa9c5a146769a96032c93141cea3797ebb642e2824dfea50
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