readme: # PsychBERT
  This domain adapted language model is pretrained from the `bert-base-cased` checkpoint on masked language modeling, using a dataset of ~40,000 PubMed papers in the domain of psychology, psychiatry, mental health, and behavioral health; as well as a dastaset of roughly 200,000 social media conversations about mental health. This work is submitted as an entry for BIBM 2021.
  
  **Note**: the token-prediction widget on this page does not work with Flax models. In order to use the model, please pull it into a Python session as follows:
  
  ```
  from transformers import FlaxAutoModelForMaskedLM, AutoModelForMaskedLM
  
  # load as a flax model
  flax_lm = FlaxAutoModelForMaskedLM.from_pretrained('mnaylor/psychbert-cased')
  
  # load as a pytorch model 
  # requires flax to be installed in your environment
  pytorch_lm = AutoModelForMaskedLM.from_pretrained('mnaylor/psychbert-cased', from_flax=True)
  ```
  
  Authors: Vedant Vajre, Mitch Naylor, Uday Kamath, Amarda Shehu