Fill-Mask
Transformers
PyTorch
Safetensors
Urdu
roberta
urdu
masked-language-modeling
encoder
dunbaabert
Instructions to use DunbaaBERT/DunbaaBERT_96k_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunbaaBERT/DunbaaBERT_96k_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="DunbaaBERT/DunbaaBERT_96k_base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("DunbaaBERT/DunbaaBERT_96k_base") model = AutoModelForMaskedLM.from_pretrained("DunbaaBERT/DunbaaBERT_96k_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from DunbaaBERT/DunbaaBERT_96k_base: direct link, hf CLI and curl.
- Browser
- Download file 640 MB
-
https://huggingface.co/DunbaaBERT/DunbaaBERT_96k_base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://DunbaaBERT/DunbaaBERT_96k_base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/DunbaaBERT/DunbaaBERT_96k_base/resolve/main/pytorch_model.bin
640 MB
- Xet hash:
- 20f4fcb1ecc135b133888c86b84967262f92c8b850572a6028533c64346907fb
- Size of remote file:
- 640 MB
- SHA256:
- 77dc31627b1078ee22238896df9426a8e8a4561f889c0e1148b5264d1db2060a
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