# Model

<!-- Provide a quick summary of what the model is/does. -->

This is a bert model that is trained on 10GB of Pakistan-Legal-Corpus on NSP and MLM tasks by **AI SYSTEMS**.

## Model Details

This model was orignally taken from "legal-bert-small-uncased" (https://huggingface.co/nlpaueb/legal-bert-small-uncased) and 
was further pretrained using the original Bert paper for NSP amd MLM task.
{"language": ["en"], "license": "openrail", "library_name": "transformers", "tags": ["legal"], "pipeline_tag": "fill-mask"}
transformers pytorch bert pretraining legal fill-mask en license:openrail endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #pretraining #legal #fill-mask #en #license-openrail #endpoints_compatible #region-us 

# Model



This is a bert model that is trained on 10GB of Pakistan-Legal-Corpus on NSP and MLM tasks by AI SYSTEMS.

## Model Details

This model was orignally taken from "legal-bert-small-uncased" (URL and 
was further pretrained using the original Bert paper for NSP amd MLM task.
# Model



This is a bert model that is trained on 10GB of Pakistan-Legal-Corpus on NSP and MLM tasks by AI SYSTEMS. ## Model Details

This model was orignally taken from "legal-bert-small-uncased" (URL and 
was further pretrained using the original Bert paper for NSP amd MLM task.
TAGS
#transformers #pytorch #bert #pretraining #legal #fill-mask #en #license-openrail #endpoints_compatible #region-us 
 # Model



This is a bert model that is trained on 10GB of Pakistan-Legal-Corpus on NSP and MLM tasks by AI SYSTEMS. ## Model Details

This model was orignally taken from "legal-bert-small-uncased" (URL and 
was further pretrained using the original Bert paper for NSP amd MLM task.
TAGS
#transformers #pytorch #bert #pretraining #legal #fill-mask #en #license-openrail #endpoints_compatible #region-us 
# Model



This is a bert model that is trained on 10GB of Pakistan-Legal-Corpus on NSP and MLM tasks by AI SYSTEMS.## Model Details

This model was orignally taken from "legal-bert-small-uncased" (URL and 
was further pretrained using the original Bert paper for NSP amd MLM task.