Description
This pretrained pipeline is a built on top of the jsl_meds_ner_vlm_2b_q16_v2 model.
How to use
from sparknlp.pretrained import PretrainedPipeline
from sparknlp_jsl.utils import vision_llm_preprocessor
prompt = """
# Template:
{
"Patient Name": "string",
"Patient Age": "integer",
"Patient Gender": "string",
"Hospital Number": "string",
"Episode Number": "string",
"Episode Date": "date-time"
}
# Context:
<image>
"""
input_df = vision_llm_preprocessor(
spark=spark,
images_path="images",
prompt=prompt,
output_col_name="prompt"
)
pipeline = PretrainedPipeline("jsl_meds_ner_vlm_2b_q16_v2_pipeline", "en", "clinical/models")
result = pipeline.transform(input_df)
from johnsnowlabs import nlp
prompt = """
# Template:
{
"Patient Name": "string",
"Patient Age": "integer",
"Patient Gender": "string",
"Hospital Number": "string",
"Episode Number": "string",
"Episode Date": "date-time"
}
# Context:
<image>
"""
input_df = nlp.vision_llm_preprocessor(
spark=spark,
images_path="images",
prompt=prompt,
output_col_name="prompt"
)
pipeline = nlp.PretrainedPipeline("jsl_meds_ner_vlm_2b_q16_v2_pipeline", "en", "clinical/models")
result = pipeline.transform(input_df)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
import com.johnsnowlabs.nlp.util.VisionLLMPreprocessor
val prompt = """
# Template:
{
"Patient Name": "string",
"Patient Age": "integer",
"Patient Gender": "string",
"Hospital Number": "string",
"Episode Number": "string",
"Episode Date": "date-time"
}
# Context:
<image>
"""
val inputDF = VisionLLMPreprocessor(
spark = spark,
imagesPath = "images",
prompt = prompt,
outputColName = "prompt"
)
val pipeline = new PretrainedPipeline("jsl_meds_ner_vlm_2b_q16_v2_pipeline", "en", "clinical/models")
val result = pipeline.transform(inputDF)
Results
{
"Patient Name": "Ms RUKHSANA SHAHEEN",
"Patient Age": 56,
"Patient Gender": "Female",
"Hospital Number": "MH005990453",
"Episode Number": "030000528270",
"Episode Date": "2021-07-02T08:31:00"
}
Model Information
| Model Name: | jsl_meds_ner_vlm_2b_q16_v2_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 6.1.0+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 3.5 GB |
Included Models
- DocumentAssembler
- ImageAssembler
- MedicalVisionLLM