This model was derived from the bert-base-uncased checkpoint by replacing the GELU with ReLU activation function and further pre-training through several iterations to adapt it to the change of the activation function.
{"language": "en", "license": "apache-2.0", "library_name": "transformers", "tags": ["fill-mask"], "datasets": ["bookcorpus", "wikipedia"]}
transformers pytorch bert fill-mask en dataset:bookcorpus dataset:wikipedia license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #fill-mask #en #dataset-bookcorpus #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

This model was derived from the bert-base-uncased checkpoint by replacing the GELU with ReLU activation function and further pre-training through several iterations to adapt it to the change of the activation function.
TAGS
#transformers #pytorch #bert #fill-mask #en #dataset-bookcorpus #dataset-wikipedia #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
