
# Modified Bert-Base Model As Part Of A Project Regarding Open-Ended Conversation MLM (uncased)

Pretrained model on English language using a masked language modeling (MLM) objective. Based on-
  Bert's base-uncased variant with the idea of fine-tuning and tweaking the model for a specific goal.
   This model is uncased: Meaning it does not make a difference between english and English.

Disclaimer: I do not own the rights for the architecture and basic model structure. I modified it according to my needs.
  However, The model still derives from bert-base-uncased, Taken from the huggingface's library of transformers.
{"language": ["en"], "library_name": "transformers", "datasets": ["Seraphiive/FragmentOfBOOKCORPUS"], "pipeline_tag": "fill-mask"}
transformers pytorch bert fill-mask en dataset:Seraphiive/FragmentOfBOOKCORPUS autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #fill-mask #en #dataset-Seraphiive/FragmentOfBOOKCORPUS #autotrain_compatible #endpoints_compatible #region-us 


# Modified Bert-Base Model As Part Of A Project Regarding Open-Ended Conversation MLM (uncased)

Pretrained model on English language using a masked language modeling (MLM) objective. Based on-
  Bert's base-uncased variant with the idea of fine-tuning and tweaking the model for a specific goal.
   This model is uncased: Meaning it does not make a difference between english and English.

Disclaimer: I do not own the rights for the architecture and basic model structure. I modified it according to my needs.
  However, The model still derives from bert-base-uncased, Taken from the huggingface's library of transformers.
# Modified Bert-Base Model As Part Of A Project Regarding Open-Ended Conversation MLM (uncased)

Pretrained model on English language using a masked language modeling (MLM) objective. Based on-
  Bert's base-uncased variant with the idea of fine-tuning and tweaking the model for a specific goal.
   This model is uncased: Meaning it does not make a difference between english and English.

Disclaimer: I do not own the rights for the architecture and basic model structure. I modified it according to my needs.
  However, The model still derives from bert-base-uncased, Taken from the huggingface's library of transformers.
TAGS
#transformers #pytorch #bert #fill-mask #en #dataset-Seraphiive/FragmentOfBOOKCORPUS #autotrain_compatible #endpoints_compatible #region-us 
 # Modified Bert-Base Model As Part Of A Project Regarding Open-Ended Conversation MLM (uncased)

Pretrained model on English language using a masked language modeling (MLM) objective. Based on-
  Bert's base-uncased variant with the idea of fine-tuning and tweaking the model for a specific goal.
   This model is uncased: Meaning it does not make a difference between english and English.

Disclaimer: I do not own the rights for the architecture and basic model structure. I modified it according to my needs.
  However, The model still derives from bert-base-uncased, Taken from the huggingface's library of transformers.
TAGS
#transformers #pytorch #bert #fill-mask #en #dataset-Seraphiive/FragmentOfBOOKCORPUS #autotrain_compatible #endpoints_compatible #region-us 
# Modified Bert-Base Model As Part Of A Project Regarding Open-Ended Conversation MLM (uncased)

Pretrained model on English language using a masked language modeling (MLM) objective. Based on-
  Bert's base-uncased variant with the idea of fine-tuning and tweaking the model for a specific goal.
   This model is uncased: Meaning it does not make a difference between english and English.

Disclaimer: I do not own the rights for the architecture and basic model structure. I modified it according to my needs.
  However, The model still derives from bert-base-uncased, Taken from the huggingface's library of transformers.