Instructions to use ji-xin/roberta_base-RTE-two_stage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ji-xin/roberta_base-RTE-two_stage with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ji-xin/roberta_base-RTE-two_stage")# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("ji-xin/roberta_base-RTE-two_stage", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57f77709d7e289fd58659e8dc02e2e0ea597a6d47c1dfa7bb70b4be4a2a313e2
- Size of remote file:
- 1.54 kB
- SHA256:
- de0a37bb2236815a6d8060fea6dfb02c498699bac518d690a3086c970b4bd02f
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