Description
Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. xtremedistil-l6-h256-uncased-go-emotion
is a English model originally trained by jonaskoenig
.
Predicted Entities
admiration
, disappointment
, disgust
, surprise
, optimism
, remorse
, disapproval
, anger
, sadness
, amusement
, excitement
, joy
, embarrassment
, love
, confusion
, fear
, approval
, gratitude
, neutral
, caring
, desire
, nervousness
, grief
, realization
, curiosity
, annoyance
, pride
, relief
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_xtremedistil_l6_h256_uncased_go_emotion","en") \
.setInputCols(["document", "token"]) \
.setOutputCol("class")
pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded])
data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).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 sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_xtremedistil_l6_h256_uncased_go_emotion","en")
.setInputCols(Array("document", "token"))
.setOutputCol("class")
val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded))
val data = Seq("PUT YOUR STRING HERE").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("en.classify.bert.go_emotions.xtremedistiled_uncased").predict("""PUT YOUR STRING HERE""")
Model Information
Model Name: | bert_classifier_xtremedistil_l6_h256_uncased_go_emotion |
Compatibility: | Spark NLP 4.2.0+ |
License: | Open Source |
Edition: | Official |
Input Labels: | [document, token] |
Output Labels: | [class] |
Language: | en |
Size: | 47.6 MB |
Case sensitive: | false |
Max sentence length: | 256 |
References
- https://huggingface.co/jonaskoenig/xtremedistil-l6-h256-uncased-go-emotion