
# Cause-Effect Detection for Software Requirements Based on Token Classification with BERT

This model uses BERT to detect cause and effect from a single sentence. The focus of this model is the domain of software requirements engineering, however, it can also be used for other domains.

The model outputs one of the following 5 labels for each token:

Other

B-Cause

I-Cause

B-Effect

I-Effect

The source code can be found here: https://colab.research.google.com/drive/14V9Ooy3aNPsRfTK88krwsereia8cfSPc?usp=sharing
{"widget": [{"text": "If a user signs up, he will receive a confirmation email."}]}
transformers pytorch jax bert token-classification autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #jax #bert #token-classification #autotrain_compatible #endpoints_compatible #has_space #region-us 


# Cause-Effect Detection for Software Requirements Based on Token Classification with BERT

This model uses BERT to detect cause and effect from a single sentence. The focus of this model is the domain of software requirements engineering, however, it can also be used for other domains.

The model outputs one of the following 5 labels for each token:

Other

B-Cause

I-Cause

B-Effect

I-Effect

The source code can be found here: URL
# Cause-Effect Detection for Software Requirements Based on Token Classification with BERT

This model uses BERT to detect cause and effect from a single sentence. The focus of this model is the domain of software requirements engineering, however, it can also be used for other domains.

The model outputs one of the following 5 labels for each token:

Other

B-Cause

I-Cause

B-Effect

I-Effect

The source code can be found here: URL
TAGS
#transformers #pytorch #jax #bert #token-classification #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # Cause-Effect Detection for Software Requirements Based on Token Classification with BERT

This model uses BERT to detect cause and effect from a single sentence. The focus of this model is the domain of software requirements engineering, however, it can also be used for other domains.

The model outputs one of the following 5 labels for each token:

Other

B-Cause

I-Cause

B-Effect

I-Effect

The source code can be found here: URL
passage: TAGS
#transformers #pytorch #jax #bert #token-classification #autotrain_compatible #endpoints_compatible #has_space #region-us 
# Cause-Effect Detection for Software Requirements Based on Token Classification with BERT

This model uses BERT to detect cause and effect from a single sentence. The focus of this model is the domain of software requirements engineering, however, it can also be used for other domains.

The model outputs one of the following 5 labels for each token:

Other

B-Cause

I-Cause

B-Effect

I-Effect

The source code can be found here: URL