Description
This model has been trained on a curated list of clinical and biomedical datasets. It has been fine-tuned for Few-Shot Assertion but can also be utilized for other purposes, such as Classification and Retrieval-Augmented Generation (RAG).
How to use
document_assembler = DocumentAssembler()\
.setInputCol("text")\
.setOutputCol("document")
e5_embeddings = E5Embeddings.pretrained("e5_base_v2_embeddings_medical_assertion_smoking", "en", "clinical/models")\
.setInputCols(["document"])\
.setOutputCol("e5_embeddings")
pipeline = Pipeline().setStages([document_assembler, e5_embeddings])
text = [
["I feel a bit drowsy after taking an insulin."],
["Peter Parker is a nice guy and lives in New York"]
]
data = spark.createDataFrame(text).toDF("text")
result = pipeline.fit(data).transform(data)
val document_assembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val e5_embeddings = E5Embeddings.pretrained("e5_base_v2_embeddings_medical_assertion_smoking", "en", "clinical/models")
.setInputCols(Array("document"))
.setOutputCol("e5_embeddings")
val pipeline = new Pipeline().setStages(Array(document_assembler, e5_embeddings))
val result = pipeline.fit(data).transform(data)
Results
+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| embeddings|
+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
|[{sentence_embeddings, 0, 43, I feel a bit drowsy after taking an insulin., {sentence -> 0}, [0.10872599, 0.055253826, 0.020003157, 0.041003194, -0.010374628, -0.02620654, 0.01587664, 0.037322525, ...|
|[{sentence_embeddings, 0, 47, Peter Parker is a nice guy and lives in New York, {sentence -> 0}, [0.108851634, 0.052013967, 0.029346386, 0.043766238, -0.012921171, -0.01598542, 0.023271276, 0.03910...|
+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
Model Information
Model Name: | e5_base_v2_embeddings_medical_assertion_smoking |
Compatibility: | Healthcare NLP 5.3.3+ |
License: | Licensed |
Edition: | Official |
Input Labels: | [document] |
Output Labels: | [embeddings] |
Language: | en |
Size: | 393.1 MB |
Case sensitive: | false |