
# Description

NonToxicCivilBert or 'CivilBert' is a further finetuned model of bert-based-uncased using only the non-toxic data of the Jigsaw-unintended-bias dataset to make the predicted tokens less toxic. 
We are working further to make this model better and less toxic. 

# You can use it directly using the transformers:
* from transformers import AutoTokenizer, AutoModelForMaskedLM
* tokenizer = AutoTokenizer.from_pretrained("Ashokajou51/NonToxicCivilBert")
* model = AutoModelForMaskedLM.from_pretrained("Ashokajou51/NonToxicCivilBert")
{"language": ["en"], "tags": ["code", "bert", "non-toxic", "nontoxicbert"], "datasets": ["jigsaw_unintended_bias"], "pipeline_tag": "fill-mask"}
transformers pytorch safetensors bert fill-mask code non-toxic nontoxicbert en dataset:jigsaw_unintended_bias autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #bert #fill-mask #code #non-toxic #nontoxicbert #en #dataset-jigsaw_unintended_bias #autotrain_compatible #endpoints_compatible #region-us 


# Description

NonToxicCivilBert or 'CivilBert' is a further finetuned model of bert-based-uncased using only the non-toxic data of the Jigsaw-unintended-bias dataset to make the predicted tokens less toxic. 
We are working further to make this model better and less toxic. 

# You can use it directly using the transformers:
* from transformers import AutoTokenizer, AutoModelForMaskedLM
* tokenizer = AutoTokenizer.from_pretrained("Ashokajou51/NonToxicCivilBert")
* model = AutoModelForMaskedLM.from_pretrained("Ashokajou51/NonToxicCivilBert")
# Description

NonToxicCivilBert or 'CivilBert' is a further finetuned model of bert-based-uncased using only the non-toxic data of the Jigsaw-unintended-bias dataset to make the predicted tokens less toxic. 
We are working further to make this model better and less toxic. # You can use it directly using the transformers:
* from transformers import AutoTokenizer, AutoModelForMaskedLM
* tokenizer = AutoTokenizer.from_pretrained("Ashokajou51/NonToxicCivilBert")
* model = AutoModelForMaskedLM.from_pretrained("Ashokajou51/NonToxicCivilBert")
TAGS
#transformers #pytorch #safetensors #bert #fill-mask #code #non-toxic #nontoxicbert #en #dataset-jigsaw_unintended_bias #autotrain_compatible #endpoints_compatible #region-us 
 # Description

NonToxicCivilBert or 'CivilBert' is a further finetuned model of bert-based-uncased using only the non-toxic data of the Jigsaw-unintended-bias dataset to make the predicted tokens less toxic. 
We are working further to make this model better and less toxic. # You can use it directly using the transformers:
* from transformers import AutoTokenizer, AutoModelForMaskedLM
* tokenizer = AutoTokenizer.from_pretrained("Ashokajou51/NonToxicCivilBert")
* model = AutoModelForMaskedLM.from_pretrained("Ashokajou51/NonToxicCivilBert")
TAGS
#transformers #pytorch #safetensors #bert #fill-mask #code #non-toxic #nontoxicbert #en #dataset-jigsaw_unintended_bias #autotrain_compatible #endpoints_compatible #region-us 
# Description

NonToxicCivilBert or 'CivilBert' is a further finetuned model of bert-based-uncased using only the non-toxic data of the Jigsaw-unintended-bias dataset to make the predicted tokens less toxic. 
We are working further to make this model better and less toxic.# You can use it directly using the transformers:
* from transformers import AutoTokenizer, AutoModelForMaskedLM
* tokenizer = AutoTokenizer.from_pretrained("Ashokajou51/NonToxicCivilBert")
* model = AutoModelForMaskedLM.from_pretrained("Ashokajou51/NonToxicCivilBert")