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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b54ce3b5fb693f60bb12c0c67fd228a13d088528fa5f05a7872ff55d766a36ad
- Size of remote file:
- 438 MB
- SHA256:
- caaa4be00168d942689f5c30c86ebd1d427969f52d3363b83629a9aa34da740e
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