Fill-Mask
Transformers
Safetensors
English
ultrabert
encoder
masked-language-modeling
long-context
custom_code
Instructions to use dmis-lab/UltraBERT-380M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dmis-lab/UltraBERT-380M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dmis-lab/UltraBERT-380M", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dmis-lab/UltraBERT-380M", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("dmis-lab/UltraBERT-380M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download img/ultrabert_evaluation.png from dmis-lab/UltraBERT-380M: direct link, hf CLI and curl.
- Browser
- Download file 636 kB
-
https://huggingface.co/dmis-lab/UltraBERT-380M/resolve/main/img/ultrabert_evaluation.png
- Command line
-
hf download hf://dmis-lab/UltraBERT-380M/img/ultrabert_evaluation.png
-
curl -L -o ultrabert_evaluation.png https://huggingface.co/dmis-lab/UltraBERT-380M/resolve/main/img/ultrabert_evaluation.png
636 kB

- Xet hash:
- 27744a98e1b6bd993f343e860a9ec5bce04e67a349ca5e2ccfa2cef3b2288590
- Size of remote file:
- 636 kB
- SHA256:
- 1cc45266b7b37f0c619de132ee6c86eee1a1f569458b4747e8f0133542aafe24
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