Description
Pretrained ALBERT Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. albert-fa-base-v2 is a Persian model orginally trained by m3hrdadfi.
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
embeddings = AlbertEmbeddings.pretrained("albert_embeddings_albert_fa_base_v2","fa") \
.setInputCols(["document", "token"]) \
.setOutputCol("embeddings")
pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
data = spark.createDataFrame([["من عاشق جرقه NLP هستم"]]).toDF("text")
result = pipeline.fit(data).transform(data)
val documentAssembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val tokenizer = new Tokenizer()
.setInputCols(Array("document"))
.setOutputCol("token")
val embeddings = AlbertEmbeddings.pretrained("albert_embeddings_albert_fa_base_v2","fa")
.setInputCols(Array("document", "token"))
.setOutputCol("embeddings")
val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
val data = Seq("من عاشق جرقه NLP هستم").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("fa.embed.albert").predict("""من عاشق جرقه NLP هستم""")
Model Information
| Model Name: | albert_embeddings_albert_fa_base_v2 |
| Compatibility: | Spark NLP 3.4.2+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [sentence, token] |
| Output Labels: | [bert] |
| Language: | fa |
| Size: | 69.2 MB |
| Case sensitive: | false |
References
- https://huggingface.co/m3hrdadfi/albert-fa-base-v2
- https://dumps.wikimedia.org/fawiki/
- https://github.com/miras-tech/MirasText
- https://bigbangpage.com/
- https://www.chetor.com/
- https://www.eligasht.com/Blog/
- https://www.digikala.com/mag/
- https://www.ted.com/talks
- https://github.com/m3hrdadfi/albert-persian
- https://github.com/hooshvare/parsbert
- https://github.com/m3hrdadfi/albert-persian