Description
This is a text-to-text model based on T5 fine-tuned to generate informal text from a formal text input, for the task “transfer Casual to Formal:”. It is based on Prithiviraj Damodaran’s Styleformer.
Predicted Entities
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How to use
import sparknlp
from sparknlp.base import *
from sparknlp.annotator import *
spark = sparknlp.start()
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("documents")
t5 = T5Transformer.pretrained("t5_informal_to_formal_styletransfer") \
.setTask("transfer Casual to Formal:") \
.setInputCols(["documents"]) \
.setMaxOutputLength(200) \
.setOutputCol("transfers")
pipeline = Pipeline().setStages([documentAssembler, t5])
data = spark.createDataFrame([["Who gives a crap?"]]).toDF("text")
result = pipeline.fit(data).transform(data)
result.select("transfers.result").show(truncate=False)
Results
+------------+
|result |
+------------+
|[Who cares?]|
+------------+
Model Information
| Model Name: | t5_informal_to_formal_styletransfer |
| Compatibility: | Spark NLP 3.4.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [documents] |
| Output Labels: | [summaries] |
| Language: | en |
| Size: | 924.0 MB |
Data Source
The original model is from the transformers library:
https://huggingface.co/prithivida/informal_to_formal_styletransfer