Instructions to use KamrusSamad/bnbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KamrusSamad/bnbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="KamrusSamad/bnbert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("KamrusSamad/bnbert") model = AutoModelForMaskedLM.from_pretrained("KamrusSamad/bnbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from KamrusSamad/bnbert: direct link, hf CLI and curl.
- Browser
- Download file 58 MB
-
https://huggingface.co/KamrusSamad/bnbert/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://KamrusSamad/bnbert@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/KamrusSamad/bnbert/resolve/refs%2Fpr%2F1/pytorch_model.bin
58 MB
- Xet hash:
- 48e2c3eefce913b7221f910670c4007d5a10052e54199a8bc3b94dea3a904b21
- Size of remote file:
- 58 MB
- SHA256:
- e60d3d92fbe7d1764b6b8d325d33c92784cddb30881b3cf60a9491a204d8c5a7
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