2022-02-03-w2v_cc_300d_fr

docs/_posts/luca-martial/2022-02-03-w2v_cc_300d_fr.md

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+---
+layout: model
+title: Fastext Word Embeddings in French
+author: John Snow Labs
+name: w2v_cc_300d
+date: 2022-02-03
+tags: [fr, open_source]
+task: Embeddings
+language: fr
+edition: Spark NLP 3.4.0
+spark_version: 3.0
+supported: true
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Word Embeddings lookup annotator that maps tokens to vectors.
+
+## Predicted Entities
+
+
+
+{:.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/public/models/w2v_cc_300d_fr_3.4.0_3.0_1643891127135.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler()\
+    .setInputCol("text")\
+    .setOutputCol("document")
+
+tokenizer = Tokenizer()\
+    .setInputCols("document")\
+    .setOutputCol("token")
+
+embeddings = WordEmbeddingsModel.pretrained("w2v_cc_300d", "fr")\
+    .setInputCols(["document", "token"])\
+    .setOutputCol("embeddings")
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val embeddings = WordEmbeddingsModel.pretrained("w2v_cc_300d", "fr")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("embeddings")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|w2v_cc_300d|
+|Type:|embeddings|
+|Compatibility:|Spark NLP 3.4.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[embeddings]|
+|Language:|fr|
+|Size:|1.3 GB|
+|Case sensitive:|false|
+|Dimension:|300|
+
+## References
+
+[FastText common crawl word embeddings for French](https://fasttext.cc/docs/en/crawl-vectors.html).