Fill-Mask
Transformers
PyTorch
Safetensors
English
bert
climate-change
domain-adaptation
masked-language-modeling
scientific-nlp
transformer
BERT
SciBERT
Eval Results (legacy)
Instructions to use P0L3/cliscibert_scivocab_uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use P0L3/cliscibert_scivocab_uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="P0L3/cliscibert_scivocab_uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("P0L3/cliscibert_scivocab_uncased") model = AutoModelForMaskedLM.from_pretrained("P0L3/cliscibert_scivocab_uncased") - Notebooks
- Google Colab
- Kaggle
Ctrl+K