# Cross-Encoder

The model can be used for Information Retrieval: given a query, encode the query will all possible passages. Then sort the passages in a decreasing order.

<p align="center">
    <img src="https://www.exibart.com/repository/media/2020/07/bridget-riley-cool-edge.jpg" width="400"> </br>
    Bridget Riley, COOL EDGE
</p>

## Training Data

This model was trained on a custom biomedical ranking dataset.

## Usage and Performance

```python
from sentence_transformers import CrossEncoder
model = CrossEncoder('efederici/cross-encoder-distilbert-it')
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')`.
{"language": ["it"], "license": "apache-2.0", "tags": ["cross-encoder", "sentence-similarity", "transformers"], "pipeline_tag": "text-classification"}
transformers pytorch safetensors distilbert text-classification cross-encoder sentence-similarity it license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #distilbert #text-classification #cross-encoder #sentence-similarity #it #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

# Cross-Encoder

The model can be used for Information Retrieval: given a query, encode the query will all possible passages. Then sort the passages in a decreasing order.

<p align="center">
    <img src="URL width="400"> </br>
    Bridget Riley, COOL EDGE
</p>

## Training Data

This model was trained on a custom biomedical ranking dataset.

## Usage and Performance



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

The model can be used for Information Retrieval: given a query, encode the query will all possible passages. Then sort the passages in a decreasing order.

<p align="center">
    <img src="URL width="400"> </br>
    Bridget Riley, COOL EDGE
</p> ## Training Data

This model was trained on a custom biomedical ranking dataset. ## Usage and Performance



The model will predict scores for the pairs '('Sentence 1', 'Sentence 2')' and '('Sentence 3', 'Sentence 4')'.
TAGS
#transformers #pytorch #safetensors #distilbert #text-classification #cross-encoder #sentence-similarity #it #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # Cross-Encoder

The model can be used for Information Retrieval: given a query, encode the query will all possible passages. Then sort the passages in a decreasing order.

<p align="center">
    <img src="URL width="400"> </br>
    Bridget Riley, COOL EDGE
</p> ## Training Data

This model was trained on a custom biomedical ranking dataset. ## Usage and Performance



The model will predict scores for the pairs '('Sentence 1', 'Sentence 2')' and '('Sentence 3', 'Sentence 4')'.
passage: TAGS
#transformers #pytorch #safetensors #distilbert #text-classification #cross-encoder #sentence-similarity #it #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# Cross-Encoder

The model can be used for Information Retrieval: given a query, encode the query will all possible passages. Then sort the passages in a decreasing order.

<p align="center">
    <img src="URL width="400"> </br>
    Bridget Riley, COOL EDGE
</p>## Training Data

This model was trained on a custom biomedical ranking dataset.## Usage and Performance



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