<commit_before>---
layout: model
title: Embeddings Sciwiki 50 dims
author: <NAME>
name: embeddings_sciwiki_50d
class: WordEmbeddingsModel
language: es
repository: clinical/models
date: 2020-05-27
tags: [clinical,embeddings,es]
article_header:
   type: cover
use_language_switcher: "Python-Scala-Java"
---

{:.h2_title}
## Description
Word Embeddings lookup annotator that maps tokens to vectors.


{:.btn-box}
<button class="button button-orange" disabled>Live Demo</button>
<button class="button button-orange" disabled>Open in Colab</button>
[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/embeddings_sciwiki_50d_es_2.5.0_2.4_1590609287349.zip){:.button.button-orange.button-orange-trans.arr.button-icon}

{:.h2_title}
## How to use 
<div class="tabs-box" markdown="1">

{% include programmingLanguageSelectScalaPython.html %}

```python
model = WordEmbeddingsModel.pretrained("embeddings_sciwiki_50d","es","clinical/models")\
	.setInputCols(["document","token"])\
	.setOutputCol("word_embeddings")
```

```scala
val model = WordEmbeddingsModel.pretrained("embeddings_sciwiki_50d","es","clinical/models")
	.setInputCols("document","token")
	.setOutputCol("word_embeddings")
```
</div>

{:.h2_title}
## Results 
Word2Vec feature vectors based on ``embeddings_sciwiki_50d``.

{:.model-param}
## Model Information

{:.table-model}
|---------------|------------------------|
| Name:          | embeddings_sciwiki_50d |
| Type:   | WordEmbeddingsModel    |
| Compatibility: | Spark NLP 2.5.0+                 |
| License:       | Licensed               |
| Edition:       | Official             |
|Input labels:        | [document, token]        |
|Output labels:       | [word_embeddings]        |
| Language:      | es                     |
| Dimension:    | 50.0                   |

{:.h2_title}
## Data Source
Trained on Clinical Wikipedia Articles
https://zenodo.org/record/3744326#.XtViinVKh_U<commit_msg>[skip_ci] new metadata lines added to 71.file 2020-05-27-embeddings_sciwiki_50d_es.md<commit_after>---
layout: model
title: Embeddings Sciwiki 50 dims
author: <NAME>
name: embeddings_sciwiki_50d
class: WordEmbeddingsModel
language: es
repository: clinical/models
date: 2020-05-27
task: Embeddings
edition: Spark NLP for Healthcare 2.5.0
tags: [clinical,embeddings,es]
article_header:
   type: cover
use_language_switcher: "Python-Scala-Java"
---

{:.h2_title}
## Description
Word Embeddings lookup annotator that maps tokens to vectors.


{:.btn-box}
<button class="button button-orange" disabled>Live Demo</button>
<button class="button button-orange" disabled>Open in Colab</button>
[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/embeddings_sciwiki_50d_es_2.5.0_2.4_1590609287349.zip){:.button.button-orange.button-orange-trans.arr.button-icon}

{:.h2_title}
## How to use 
<div class="tabs-box" markdown="1">

{% include programmingLanguageSelectScalaPython.html %}

```python
model = WordEmbeddingsModel.pretrained("embeddings_sciwiki_50d","es","clinical/models")\
	.setInputCols(["document","token"])\
	.setOutputCol("word_embeddings")
```

```scala
val model = WordEmbeddingsModel.pretrained("embeddings_sciwiki_50d","es","clinical/models")
	.setInputCols("document","token")
	.setOutputCol("word_embeddings")
```
</div>

{:.h2_title}
## Results 
Word2Vec feature vectors based on ``embeddings_sciwiki_50d``.

{:.model-param}
## Model Information

{:.table-model}
|---------------|------------------------|
| Name:          | embeddings_sciwiki_50d |
| Type:   | WordEmbeddingsModel    |
| Compatibility: | Spark NLP 2.5.0+                 |
| License:       | Licensed               |
| Edition:       | Official             |
|Input labels:        | [document, token]        |
|Output labels:       | [word_embeddings]        |
| Language:      | es                     |
| Dimension:    | 50.0                   |

{:.h2_title}
## Data Source
Trained on Clinical Wikipedia Articles
https://zenodo.org/record/3744326#.XtViinVKh_U
{'fraction_non_alphanumeric': 0.15755305867665417, 'fraction_numerical': 0.033707865168539325, 'mean_word_length': 3.588774341351661, 'pattern_counts': {'":': 0, '<': 17, '<?xml version=': 0, '>': 17, 'https://': 4, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 2, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '3102235', 'n_tokens_mistral': 1474, 'n_tokens_neox': 1299, 'n_words': 246}