Instructions to use citiusLTL/DisorBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use citiusLTL/DisorBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="citiusLTL/DisorBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("citiusLTL/DisorBERT") model = AutoModelForMaskedLM.from_pretrained("citiusLTL/DisorBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8473709fae2b651781ec4c21a1f2d79431f4a835e4823018ce6339b04f644164
- Size of remote file:
- 3.45 kB
- SHA256:
- 80d7776d81f7b1c98024df61f5c3f530f749913005b5ceb75708639e7f7bb7c4
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