Fill-Mask
Transformers
PyTorch
Safetensors
English
roberta
scientific
scholarly
encoder
masked-lm
scientific-language-processing
Eval Results (legacy)
Instructions to use scilons/SciLaD-M-custom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scilons/SciLaD-M-custom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="scilons/SciLaD-M-custom")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("scilons/SciLaD-M-custom") model = AutoModelForMaskedLM.from_pretrained("scilons/SciLaD-M-custom", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Ctrl+K