# Cross-Encoder for Quora Duplicate Questions Detection
This model was trained using [SentenceTransformers](https://sbert.net) [Cross-Encoder](https://www.sbert.net/examples/applications/cross-encoder/README.html) class.

## Training Data
This model was trained on the [STS benchmark dataset](http://ixa2.si.ehu.eus/stswiki/index.php/STSbenchmark). The model will predict a score between 0 and 1 how for the semantic similarity of two sentences. 


## Usage and Performance

Pre-trained models can be used like this:
```
from sentence_transformers import CrossEncoder
model = CrossEncoder('model_name')
scores = model.predict([('Sentence 1', 'Sentence 2'), ('Sentence 3', 'Sentence 4')])
```

The model will predict scores for the pairs `('Sentence 1', 'Sentence 2')` and `('Sentence 3', 'Sentence 4')`.

You can use this model also without sentence_transformers and by just using Transformers ``AutoModel`` class
{"license": "apache-2.0"}
transformers pytorch jax roberta text-classification license:apache-2.0 autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #jax #roberta #text-classification #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 

# Cross-Encoder for Quora Duplicate Questions Detection
This model was trained using SentenceTransformers Cross-Encoder class.

## Training Data
This model was trained on the STS benchmark dataset. The model will predict a score between 0 and 1 how for the semantic similarity of two sentences. 


## Usage and Performance

Pre-trained models can be used like this:


The model will predict scores for the pairs '('Sentence 1', 'Sentence 2')' and '('Sentence 3', 'Sentence 4')'.

You can use this model also without sentence_transformers and by just using Transformers ''AutoModel'' class
# Cross-Encoder for Quora Duplicate Questions Detection
This model was trained using SentenceTransformers Cross-Encoder class. ## Training Data
This model was trained on the STS benchmark dataset. The model will predict a score between 0 and 1 how for the semantic similarity of two sentences. ## Usage and Performance

Pre-trained models can be used like this:


The model will predict scores for the pairs '('Sentence 1', 'Sentence 2')' and '('Sentence 3', 'Sentence 4')'.

You can use this model also without sentence_transformers and by just using Transformers ''AutoModel'' class
TAGS
#transformers #pytorch #jax #roberta #text-classification #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # Cross-Encoder for Quora Duplicate Questions Detection
This model was trained using SentenceTransformers Cross-Encoder class. ## Training Data
This model was trained on the STS benchmark dataset. The model will predict a score between 0 and 1 how for the semantic similarity of two sentences. ## Usage and Performance

Pre-trained models can be used like this:


The model will predict scores for the pairs '('Sentence 1', 'Sentence 2')' and '('Sentence 3', 'Sentence 4')'.

You can use this model also without sentence_transformers and by just using Transformers ''AutoModel'' class
passage: TAGS
#transformers #pytorch #jax #roberta #text-classification #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
# Cross-Encoder for Quora Duplicate Questions Detection
This model was trained using SentenceTransformers Cross-Encoder class.## Training Data
This model was trained on the STS benchmark dataset. The model will predict a score between 0 and 1 how for the semantic similarity of two sentences.## Usage and Performance

Pre-trained models can be used like this:


The model will predict scores for the pairs '('Sentence 1', 'Sentence 2')' and '('Sentence 3', 'Sentence 4')'.

You can use this model also without sentence_transformers and by just using Transformers ''AutoModel'' class