Instructions to use jmzk96/PCSciBERT_cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jmzk96/PCSciBERT_cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jmzk96/PCSciBERT_cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jmzk96/PCSciBERT_cased") model = AutoModelForMaskedLM.from_pretrained("jmzk96/PCSciBERT_cased") - Notebooks
- Google Colab
- Kaggle
Upload pytorch_model.bin
Browse files- pytorch_model.bin +3 -0
pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:c8f3635d00c82f48f46b26a3b038a84ab4a216ff2d16955695ad9705e2558a84
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size 439957753
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