Instructions to use KISTI-AI/scideberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KISTI-AI/scideberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="KISTI-AI/scideberta")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("KISTI-AI/scideberta") model = AutoModelForMaskedLM.from_pretrained("KISTI-AI/scideberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 667ec150f3da80c4f32ad32e5b54d306e47b3a0d3b27417650c096bc27a6a42e
- Size of remote file:
- 557 MB
- SHA256:
- 6c087ce4401dcc35034db9668e02f610698dafa74d578e88ef38ecac74badd4e
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