๐จ Data Designer 101: Seeding Synthetic Data Generation with an External Datasetยถ
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๐ What you'll learnยถ
In this notebook, we will demonstrate how to seed synthetic data generation in Data Designer with an external dataset.
If this is your first time using Data Designer, we recommend starting with the first notebook in this 101 series.
๐ฆ Import the essentialsยถ
- The
essentialsmodule provides quick access to the most commonly used objects.
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from data_designer.essentials import (
DataDesigner,
DataDesignerConfigBuilder,
InferenceParameters,
ModelConfig,
SeedConfig,
)
from data_designer.essentials import (
DataDesigner,
DataDesignerConfigBuilder,
InferenceParameters,
ModelConfig,
SeedConfig,
)
โ๏ธ Initialize the Data Designer interfaceยถ
DataDesigneris the main object that is used to interface with the library.
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data_designer_client = DataDesigner()
data_designer_client = DataDesigner()
[16:33:56] [INFO] โป๏ธ Using default model providers from '/Users/amanoel/.data-designer/model_providers.yaml'
๐๏ธ Define model configurationsยถ
Each
ModelConfigdefines a model that can be used during the generation process.The "model alias" is used to reference the model in the Data Designer config (as we will see below).
The "model provider" is the external service that hosts the model (see the model config docs for more details).
By default, we use build.nvidia.com as the model provider.
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# This name is set in the model provider configuration.
MODEL_PROVIDER = "nvidia"
# The model ID is from build.nvidia.com.
MODEL_ID = "nvidia/nvidia-nemotron-nano-9b-v2"
# We choose this alias to be descriptive for our use case.
MODEL_ALIAS = "nemotron-nano-v2"
# This sets reasoning to False for the nemotron-nano-v2 model.
SYSTEM_PROMPT = "/no_think"
model_configs = [
ModelConfig(
alias=MODEL_ALIAS,
model=MODEL_ID,
provider=MODEL_PROVIDER,
inference_parameters=InferenceParameters(
temperature=0.5,
top_p=1.0,
max_tokens=1024,
),
)
]
# This name is set in the model provider configuration.
MODEL_PROVIDER = "nvidia"
# The model ID is from build.nvidia.com.
MODEL_ID = "nvidia/nvidia-nemotron-nano-9b-v2"
# We choose this alias to be descriptive for our use case.
MODEL_ALIAS = "nemotron-nano-v2"
# This sets reasoning to False for the nemotron-nano-v2 model.
SYSTEM_PROMPT = "/no_think"
model_configs = [
ModelConfig(
alias=MODEL_ALIAS,
model=MODEL_ID,
provider=MODEL_PROVIDER,
inference_parameters=InferenceParameters(
temperature=0.5,
top_p=1.0,
max_tokens=1024,
),
)
]
๐๏ธ Initialize the Data Designer Config Builderยถ
The Data Designer config defines the dataset schema and generation process.
The config builder provides an intuitive interface for building this configuration.
The list of model configs is provided to the builder at initialization.
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config_builder = DataDesignerConfigBuilder(model_configs=model_configs)
config_builder = DataDesignerConfigBuilder(model_configs=model_configs)
๐ฅ Prepare a seed datasetยถ
For this notebook, we'll create a synthetic dataset of patient notes.
We will seed the generation process with a symptom-to-diagnosis dataset.
We already have the dataset downloaded in the data directory of this repository.
๐ฑ Why use a seed dataset?
Seed datasets let you steer the generation process by providing context that is specific to your use case.
Seed datasets are also an excellent way to inject real-world diversity into your synthetic data.
During generation, prompt templates can reference any of the seed dataset fields.
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# Download sample dataset from Github
import urllib.request
url = "https://raw.githubusercontent.com/NVIDIA/GenerativeAIExamples/refs/heads/main/nemo/NeMo-Data-Designer/data/gretelai_symptom_to_diagnosis.csv"
local_filename, headers = urllib.request.urlretrieve(url, "gretelai_symptom_to_diagnosis.csv")
seed_dataset = SeedConfig(dataset=local_filename)
# Pass the reference to the config builder for use during generation.
config_builder.with_seed_dataset(seed_dataset)
# Download sample dataset from Github
import urllib.request
url = "https://raw.githubusercontent.com/NVIDIA/GenerativeAIExamples/refs/heads/main/nemo/NeMo-Data-Designer/data/gretelai_symptom_to_diagnosis.csv"
local_filename, headers = urllib.request.urlretrieve(url, "gretelai_symptom_to_diagnosis.csv")
seed_dataset = SeedConfig(dataset=local_filename)
# Pass the reference to the config builder for use during generation.
config_builder.with_seed_dataset(seed_dataset)
Out[5]:
DataDesignerConfigBuilder( seed_dataset: 'gretelai_symptom_to_diagnosis.csv' seed_dataset_columns: ['diagnosis', 'patient_summary'] )
๐จ Designing our synthetic patient notes datasetยถ
Here we use
add_columnwith keyword arguments (rather than imported config objects).Generally, we recommend using concrete objects, but this is a convenient shorthand.
Note: The prompt template can reference fields from our seed dataset:
{{ diagnosis }}- the medical diagnosis from the seed data{{ patient_summary }}- the symptom description from the seed data
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config_builder.add_column(
name="patient_sampler",
column_type="sampler",
sampler_type="person_from_faker",
)
config_builder.add_column(
name="doctor_sampler",
column_type="sampler",
sampler_type="person_from_faker",
)
config_builder.add_column(
name="patient_id",
column_type="sampler",
sampler_type="uuid",
params={
"prefix": "PT-",
"short_form": True,
"uppercase": True,
},
)
config_builder.add_column(
name="first_name",
column_type="expression",
expr="{{ patient_sampler.first_name}}",
)
config_builder.add_column(
name="last_name",
column_type="expression",
expr="{{ patient_sampler.last_name }}",
)
config_builder.add_column(
name="dob",
column_type="expression",
expr="{{ patient_sampler.birth_date }}",
)
config_builder.add_column(
name="symptom_onset_date",
column_type="sampler",
sampler_type="datetime",
params={"start": "2024-01-01", "end": "2024-12-31"},
)
config_builder.add_column(
name="date_of_visit",
column_type="sampler",
sampler_type="timedelta",
params={"dt_min": 1, "dt_max": 30, "reference_column_name": "symptom_onset_date"},
)
config_builder.add_column(
name="physician",
column_type="expression",
expr="Dr. {{ doctor_sampler.last_name }}",
)
config_builder.add_column(
name="physician_notes",
column_type="llm-text",
prompt="""\
You are a primary-care physician who just had an appointment with {{ first_name }} {{ last_name }},
who has been struggling with symptoms from {{ diagnosis }} since {{ symptom_onset_date }}.
The date of today's visit is {{ date_of_visit }}.
{{ patient_summary }}
Write careful notes about your visit with {{ first_name }},
as Dr. {{ doctor_sampler.first_name }} {{ doctor_sampler.last_name }}.
Format the notes as a busy doctor might.
""",
model_alias=MODEL_ALIAS,
system_prompt=SYSTEM_PROMPT,
)
config_builder.validate()
config_builder.add_column(
name="patient_sampler",
column_type="sampler",
sampler_type="person_from_faker",
)
config_builder.add_column(
name="doctor_sampler",
column_type="sampler",
sampler_type="person_from_faker",
)
config_builder.add_column(
name="patient_id",
column_type="sampler",
sampler_type="uuid",
params={
"prefix": "PT-",
"short_form": True,
"uppercase": True,
},
)
config_builder.add_column(
name="first_name",
column_type="expression",
expr="{{ patient_sampler.first_name}}",
)
config_builder.add_column(
name="last_name",
column_type="expression",
expr="{{ patient_sampler.last_name }}",
)
config_builder.add_column(
name="dob",
column_type="expression",
expr="{{ patient_sampler.birth_date }}",
)
config_builder.add_column(
name="symptom_onset_date",
column_type="sampler",
sampler_type="datetime",
params={"start": "2024-01-01", "end": "2024-12-31"},
)
config_builder.add_column(
name="date_of_visit",
column_type="sampler",
sampler_type="timedelta",
params={"dt_min": 1, "dt_max": 30, "reference_column_name": "symptom_onset_date"},
)
config_builder.add_column(
name="physician",
column_type="expression",
expr="Dr. {{ doctor_sampler.last_name }}",
)
config_builder.add_column(
name="physician_notes",
column_type="llm-text",
prompt="""\
You are a primary-care physician who just had an appointment with {{ first_name }} {{ last_name }},
who has been struggling with symptoms from {{ diagnosis }} since {{ symptom_onset_date }}.
The date of today's visit is {{ date_of_visit }}.
{{ patient_summary }}
Write careful notes about your visit with {{ first_name }},
as Dr. {{ doctor_sampler.first_name }} {{ doctor_sampler.last_name }}.
Format the notes as a busy doctor might.
""",
model_alias=MODEL_ALIAS,
system_prompt=SYSTEM_PROMPT,
)
config_builder.validate()
[16:33:57] [INFO] โ Validation passed
Out[ย ]:
DataDesignerConfigBuilder( seed_dataset: 'gretelai_symptom_to_diagnosis.csv' seed_dataset_columns: ['diagnosis', 'patient_summary'] sampler_columns: [ "patient_sampler", "doctor_sampler", "patient_id", "symptom_onset_date", "date_of_visit" ] llm_text_columns: ['physician_notes'] expression_columns: [ "first_name", "last_name", "dob", "physician" ] )
๐ Iteration is key โย preview the dataset!ยถ
Use the
previewmethod to generate a sample of records quickly.Inspect the results for quality and format issues.
Adjust column configurations, prompts, or parameters as needed.
Re-run the preview until satisfied.
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preview = data_designer_client.preview(config_builder)
preview = data_designer_client.preview(config_builder)
[16:33:57] [INFO] ๐ธ Preview generation in progress
[16:33:57] [INFO] โ
Validation passed
[16:33:57] [INFO] โ๏ธ Sorting column configs into a Directed Acyclic Graph
[16:33:57] [INFO] ๐ฉบ Running health checks for models...
[16:33:57] [INFO] |-- ๐ Checking 'nvidia/nvidia-nemotron-nano-9b-v2' in provider named 'nvidia' for model alias 'nemotron-nano-v2'...
[16:33:58] [INFO] |-- โ
Passed!
[16:33:58] [INFO] ๐ฑ Sampling 10 records from seed dataset
[16:33:58] [INFO] |-- seed dataset size: 820 records
[16:33:58] [INFO] |-- sampling strategy: ordered
[16:33:58] [INFO] ๐ฒ Preparing samplers to generate 10 records across 5 columns
[16:33:58] [INFO] (๐พ + ๐พ) Concatenating 2 datasets
[16:33:58] [INFO] ๐งฉ Generating column `first_name` from expression
[16:33:58] [INFO] ๐งฉ Generating column `last_name` from expression
[16:33:58] [INFO] ๐งฉ Generating column `dob` from expression
[16:33:58] [INFO] ๐งฉ Generating column `physician` from expression
[16:33:58] [INFO] ๐ Preparing llm-text column generation
[16:33:58] [INFO] |-- column name: 'physician_notes'
[16:33:58] [INFO] |-- model config:
{
"alias": "nemotron-nano-v2",
"model": "nvidia/nvidia-nemotron-nano-9b-v2",
"inference_parameters": {
"temperature": 0.5,
"top_p": 1.0,
"max_tokens": 1024,
"max_parallel_requests": 4,
"timeout": null,
"extra_body": null
},
"provider": "nvidia"
}
[16:33:58] [INFO] ๐ Processing llm-text column 'physician_notes' with 4 concurrent workers
[16:34:20] [INFO] ๐ Model usage summary:
{
"nvidia/nvidia-nemotron-nano-9b-v2": {
"token_usage": {
"prompt_tokens": 1304,
"completion_tokens": 7898,
"total_tokens": 9202
},
"request_usage": {
"successful_requests": 10,
"failed_requests": 0,
"total_requests": 10
},
"tokens_per_second": 412,
"requests_per_minute": 26
}
}
[16:34:20] [INFO] ๐ Measuring dataset column statistics:
[16:34:20] [INFO] |-- ๐ฑ column: 'diagnosis'
[16:34:20] [INFO] |-- ๐ฑ column: 'patient_summary'
[16:34:20] [INFO] |-- ๐ฒ column: 'patient_sampler'
[16:34:20] [INFO] |-- ๐ฒ column: 'doctor_sampler'
[16:34:20] [INFO] |-- ๐ฒ column: 'patient_id'
[16:34:20] [INFO] |-- ๐งฉ column: 'first_name'
[16:34:20] [INFO] |-- ๐งฉ column: 'last_name'
[16:34:20] [INFO] |-- ๐งฉ column: 'dob'
[16:34:20] [INFO] |-- ๐ฒ column: 'symptom_onset_date'
[16:34:20] [INFO] |-- ๐ฒ column: 'date_of_visit'
[16:34:20] [INFO] |-- ๐งฉ column: 'physician'
[16:34:20] [INFO] |-- ๐ column: 'physician_notes'
[16:34:20] [INFO] โ
Preview complete!
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# Run this cell multiple times to cycle through the 10 preview records.
preview.display_sample_record()
# Run this cell multiple times to cycle through the 10 preview records.
preview.display_sample_record()
Seed Columns โโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โ Name โ Value โ โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ โ diagnosis โ cervical spondylosis โ โโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ patient_summary โ I've been having a lot of pain in my neck and back. I've also been having trouble with my โ โ โ balance and coordination. I've been coughing a lot and my limbs feel weak. โ โโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ Generated Columns โโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โ Name โ Value โ โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ โ patient_sampler โ { โ โ โ 'uuid': '68174e80-5e4b-4e5c-b68f-91bec63746ef', โ โ โ 'locale': 'en_US', โ โ โ 'first_name': 'Wendy', โ โ โ 'last_name': 'Guzman', โ โ โ 'middle_name': None, โ โ โ 'sex': 'Female', โ โ โ 'street_number': '7569', โ โ โ 'street_name': 'Beth Ports', โ โ โ 'city': 'West Lauren', โ โ โ 'state': 'Arizona', โ โ โ 'postcode': '62783', โ โ โ 'age': 99, โ โ โ 'birth_date': '1926-06-11', โ โ โ 'country': 'Armenia', โ โ โ 'marital_status': 'separated', โ โ โ 'education_level': 'secondary_education', โ โ โ 'unit': '', โ โ โ 'occupation': 'Engineer, materials', โ โ โ 'phone_number': '882-478-7638', โ โ โ 'bachelors_field': 'no_degree' โ โ โ } โ โโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ doctor_sampler โ { โ โ โ 'uuid': '6b0cc640-5322-4068-8e62-408648f2a01a', โ โ โ 'locale': 'en_US', โ โ โ 'first_name': 'Katherine', โ โ โ 'last_name': 'Aguilar', โ โ โ 'middle_name': None, โ โ โ 'sex': 'Female', โ โ โ 'street_number': '174', โ โ โ 'street_name': 'Tran Shoals', โ โ โ 'city': 'Lake Ryan', โ โ โ 'state': 'Illinois', โ โ โ 'postcode': '59489', โ โ โ 'age': 106, โ โ โ 'birth_date': '1919-07-02', โ โ โ 'country': 'Mayotte', โ โ โ 'marital_status': 'never_married', โ โ โ 'education_level': 'secondary_education', โ โ โ 'unit': '', โ โ โ 'occupation': 'Archaeologist', โ โ โ 'phone_number': '001-929-429-7385', โ โ โ 'bachelors_field': 'no_degree' โ โ โ } โ โโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ patient_id โ PT-CB852B6C โ โโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ symptom_onset_date โ 2024-02-20 โ โโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ date_of_visit โ 2024-02-21 โ โโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ first_name โ Wendy โ โโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ last_name โ Guzman โ โโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ dob โ 1926-06-11 โ โโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ physician โ Dr. Aguilar โ โโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ physician_notes โ **Dr. Katherine Aguilar** โ โ โ **Primary Care Physician** โ โ โ **Visit Date:** 2024-02-21 โ โ โ **Patient:** Wendy Guzman โ โ โ โ โ โ --- โ โ โ โ โ โ **Chief Complaints:** โ โ โ - Neck and back pain since 2024-02-20 โ โ โ - Balance and coordination issues โ โ โ - Frequent coughing โ โ โ - Weakness in limbs โ โ โ โ โ โ **History of Present Illness:** โ โ โ Wendy presents with worsening cervical spondylosis symptoms, including persistent neck and โ โ โ back pain radiating to her shoulders and arms. She reports new-onset dizziness and โ โ โ imbalance, which she attributes to her neck pain. Additionally, she has been coughing โ โ โ frequently over the past few days and notes generalized weakness in her upper and lower โ โ โ extremities. She denies fever, chest pain, or shortness of breath. โ โ โ โ โ โ **Past Medical History:** โ โ โ - Chronic cervical spondylosis (diagnosed 2024-02-20) โ โ โ - No prior surgeries or hospitalizations โ โ โ - No known allergies โ โ โ โ โ โ **Medications:** โ โ โ - Ibuprofen 400mg PRN for pain โ โ โ - No other regular medications โ โ โ โ โ โ **Social History:** โ โ โ - Sedentary lifestyle due to pain โ โ โ - No smoking or alcohol use โ โ โ - Denies recent travel or exposure to sick contacts โ โ โ โ โ โ **Review of Systems:** โ โ โ - Constitutional: No fever, chills, or weight loss โ โ โ - Neurological: Weakness in arms/legs, numbness in hands, occasional tingling โ โ โ - Respiratory: Productive cough, no hemoptysis โ โ โ - Musculoskeletal: Pain with neck movement, stiffness โ โ โ โ โ โ **Physical Exam:** โ โ โ - **Vital Signs:** Temp 98.6ยฐF, HR 78, BP 128/80, RR 16, SpO2 98% on room air โ โ โ - **Neck Exam:** Limited range of motion, tenderness at C5-C6, no focal deficits โ โ โ - **Neurological:** Mild weakness in bilateral upper extremities (4/5 strength), no focal โ โ โ deficits on reflex testing โ โ โ - **Respiratory:** Clear lung fields, no wheezing or crackles โ โ โ - **Musculoskeletal:** Mild tenderness in cervical spine, no joint swelling โ โ โ โ โ โ **Assessment:** โ โ โ 1. Worsening cervical spondylosis with radicular symptoms (possible nerve root โ โ โ irritation). โ โ โ 2. New neurological symptoms (weakness, imbalance) possibly related to cervical spine โ โ โ pathology or systemic issue. โ โ โ 3. Productive cough โ differential includes upper respiratory infection, post-viral cough, โ โ โ or exacerbation of cervical spine-related dysphagia/airway irritation. โ โ โ โ โ โ **Plan:** โ โ โ 1. **Imaging:** Order MRI of the cervical spine to evaluate for disc herniation, stenosis, โ โ โ or other structural abnormalities contributing to radiculopathy. โ โ โ 2. **Neurology Referral:** For further evaluation of neurological deficits and balance โ โ โ issues. โ โ โ 3. **Respiratory Workup:** Consider chest X-ray or spirometry if cough persists or worsens โ โ โ to rule out pneumonia or other pulmonary pathology. โ โ โ 4. **Physical Therapy:** Referral for cervical spine mobilization and strengthening โ โ โ exercises. โ โ โ 5. **Pain Management:** Consider short-term prescription of a muscle relaxant or โ โ โ neuropathic agent if symptoms persist. โ โ โ 6. **Patient Education:** Advise activity modification, posture correction, and follow-up โ โ โ in 1-2 weeks or sooner if symptoms escalate. โ โ โ โ โ โ **Next Appointment:** Scheduled for 2024-03-05 or sooner if symptoms worsen. โ โ โ โ โ โ **Signature:** โ โ โ Dr. Katherine Aguilar โ โ โ Primary Care Physician โ โ โ [Contact Information] โ โ โ โ โโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ [index: 0]
Inย [9]:
Copied!
# The preview dataset is available as a pandas DataFrame.
preview.dataset
# The preview dataset is available as a pandas DataFrame.
preview.dataset
Out[9]:
| diagnosis | patient_summary | patient_sampler | doctor_sampler | patient_id | symptom_onset_date | date_of_visit | first_name | last_name | dob | physician | physician_notes | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | cervical spondylosis | I've been having a lot of pain in my neck and ... | {'uuid': '68174e80-5e4b-4e5c-b68f-91bec63746ef... | {'uuid': '6b0cc640-5322-4068-8e62-408648f2a01a... | PT-CB852B6C | 2024-02-20 | 2024-02-21 | Wendy | Guzman | 1926-06-11 | Dr. Aguilar | **Dr. Katherine Aguilar** \n**Primary Care Ph... |
| 1 | impetigo | I have a rash on my face that is getting worse... | {'uuid': '4e98c43b-8f7d-4bb4-8bd7-a7eafa0b556d... | {'uuid': '633df172-baa5-47bc-8e3b-d0b588542cdb... | PT-CF78B0FA | 2024-09-18 | 2024-09-19 | Amanda | Smith | 1994-09-27 | Dr. Marsh | **Dr. Sherri Marsh, MD** \n**Primary Care Phy... |
| 2 | urinary tract infection | I have been urinating blood. I sometimes feel ... | {'uuid': 'c1af3224-3584-4e40-a995-3460f958848d... | {'uuid': 'c59bda90-b568-4694-bf95-8fda720d6e79... | PT-12A85CCD | 2024-10-12 | 2024-10-24 | Timothy | Simmons | 1917-04-30 | Dr. Carpenter | **Dr. Elizabeth Carpenter** \n**Primary Care ... |
| 3 | arthritis | I have been having trouble with my muscles and... | {'uuid': '0ba463b6-0b83-43b7-b689-78b6d25b2f48... | {'uuid': '53f687e8-a9bd-4900-94ed-c9f23dfd0a07... | PT-FFEF37D6 | 2024-08-30 | 2024-09-05 | Patricia | White | 1984-11-27 | Dr. Oliver | **Dr. Maria Oliver** \n**Primary Care Physici... |
| 4 | dengue | I have been feeling really sick. My body hurts... | {'uuid': 'f3ec1689-8b90-495c-b41a-fc64563a088c... | {'uuid': '1e6ce90f-0907-4843-acad-7fc6325a4b5f... | PT-DC0CCE6C | 2024-12-19 | 2024-12-28 | Leah | Weaver | 1996-06-28 | Dr. Wilkins | **Dr. Christopher Wilkins** \n**Primary Care ... |
| 5 | common cold | I've been feeling really run down and weak. My... | {'uuid': '99905039-a297-4539-8541-162c9bc0b944... | {'uuid': '9824c4af-77bd-41ef-b3de-96bcef1a3afd... | PT-79573082 | 2024-09-19 | 2024-09-24 | Andrea | Morrison | 1944-07-30 | Dr. Williams | **Dr. Tristan Williams, Primary Care Physician... |
| 6 | dengue | I have rashes all over my body. I also have a ... | {'uuid': '94f729fc-c6f5-4f79-9930-cbe5b11591a5... | {'uuid': 'f95cc47e-19c6-410e-9432-22bd7b3b264f... | PT-CB395BC7 | 2024-04-27 | 2024-05-15 | Holly | Jackson | 1939-07-24 | Dr. Hoffman | **Dr. Ashley Hoffman** \n**Primary Care Physi... |
| 7 | dengue | I have been feeling nauseous and have a consta... | {'uuid': '32e44e19-e6da-4696-a7fd-d78ab2d31bd8... | {'uuid': '629f6af3-f78c-4bf6-b253-c2b253d45813... | PT-F673CE25 | 2024-09-27 | 2024-09-29 | Lance | Henderson | 1981-11-17 | Dr. Kennedy | **Dr. Kristen Kennedy** \n**Primary Care Phys... |
| 8 | impetigo | I have a rash around my nose that is red and i... | {'uuid': 'e61cefa1-254a-414b-baea-f9fa6696a854... | {'uuid': 'cbec5207-bd43-4c5c-b8b6-5129065eae6f... | PT-288E96A3 | 2024-07-14 | 2024-08-03 | Megan | Pena | 1973-09-30 | Dr. Moore | **Dr. Pamela Moore** \n**Primary Care Physici... |
| 9 | drug reaction | I have a rash on my chest and back and it itch... | {'uuid': 'c893e5ec-fa33-4acd-83de-2724eadab37e... | {'uuid': 'eaf0d824-e65a-4e22-be8c-325f3d25bff7... | PT-1DE48AF1 | 2024-02-14 | 2024-03-05 | Melvin | Thomas | 1954-07-15 | Dr. Leonard | **Dr. Blake Leonard, Primary Care Physician** ... |
๐ Analyze the generated dataยถ
Data Designer automatically generates a basic statistical analysis of the generated data.
This analysis is available via the
analysisproperty of generation result objects.
Inย [10]:
Copied!
# Print the analysis as a table.
preview.analysis.to_report()
# Print the analysis as a table.
preview.analysis.to_report()
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ ๐จ Data Designer Dataset Profile โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ Dataset Overview โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โ number of records โ number of columns โ percent complete records โ โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ โ 10 โ 12 โ 100.0% โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ ๐ฑ Seed-Dataset Columns โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โ column name โ data type โ number unique values โ โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ โ diagnosis โ string โ 7 (70.0%) โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ patient_summary โ string โ 10 (100.0%) โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ ๐ฒ Sampler Columns โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โ column name โ data type โ number unique values โ sampler type โ โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ โ patient_sampler โ dict โ 10 (100.0%) โ person_from_faker โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ doctor_sampler โ dict โ 10 (100.0%) โ person_from_faker โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ patient_id โ string โ 10 (100.0%) โ uuid โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ symptom_onset_date โ string โ 10 (100.0%) โ datetime โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ date_of_visit โ string โ 10 (100.0%) โ timedelta โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ ๐ LLM-Text Columns โโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโ โ โ โ โ prompt tokens โ completion tokens โ โ column name โ data type โ number unique values โ per record โ per record โ โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ โ physician_notes โ string โ 10 (100.0%) โ 111.0 +/- 5.6 โ 725.5 +/- 102.8 โ โโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโ ๐งฉ Expression Columns โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โ column name โ data type โ number unique values โ โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ โ first_name โ string โ 10 (100.0%) โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ last_name โ string โ 10 (100.0%) โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ dob โ string โ 10 (100.0%) โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ physician โ string โ 10 (100.0%) โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โญโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ Table Notes โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฎ โ โ โ 1. All token statistics are based on a sample of max(1000, len(dataset)) records. โ โ 2. Tokens are calculated using tiktoken's cl100k_base tokenizer. โ โ โ โฐโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฏ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
๐ Scale up!ยถ
Happy with your preview data?
Use the
createmethod to submit larger Data Designer generation jobs.
Inย [11]:
Copied!
job_results = data_designer_client.create(config_builder, num_records=20)
job_results = data_designer_client.create(config_builder, num_records=20)
[16:34:21] [INFO] ๐จ Creating Data Designer dataset
[16:34:21] [INFO] โ
Validation passed
[16:34:21] [INFO] โ๏ธ Sorting column configs into a Directed Acyclic Graph
[16:34:21] [INFO] ๐ฉบ Running health checks for models...
[16:34:21] [INFO] |-- ๐ Checking 'nvidia/nvidia-nemotron-nano-9b-v2' in provider named 'nvidia' for model alias 'nemotron-nano-v2'...
[16:34:22] [INFO] |-- โ
Passed!
[16:34:22] [INFO] โณ Processing batch 1 of 1
[16:34:22] [INFO] ๐ฑ Sampling 20 records from seed dataset
[16:34:22] [INFO] |-- seed dataset size: 820 records
[16:34:22] [INFO] |-- sampling strategy: ordered
[16:34:22] [INFO] ๐ฒ Preparing samplers to generate 20 records across 5 columns
[16:34:22] [INFO] (๐พ + ๐พ) Concatenating 2 datasets
[16:34:22] [INFO] ๐งฉ Generating column `first_name` from expression
[16:34:22] [INFO] ๐งฉ Generating column `last_name` from expression
[16:34:22] [INFO] ๐งฉ Generating column `dob` from expression
[16:34:22] [INFO] ๐งฉ Generating column `physician` from expression
[16:34:22] [INFO] ๐ Preparing llm-text column generation
[16:34:22] [INFO] |-- column name: 'physician_notes'
[16:34:22] [INFO] |-- model config:
{
"alias": "nemotron-nano-v2",
"model": "nvidia/nvidia-nemotron-nano-9b-v2",
"inference_parameters": {
"temperature": 0.5,
"top_p": 1.0,
"max_tokens": 1024,
"max_parallel_requests": 4,
"timeout": null,
"extra_body": null
},
"provider": "nvidia"
}
[16:34:22] [INFO] ๐ Processing llm-text column 'physician_notes' with 4 concurrent workers
[16:35:06] [INFO] ๐ Model usage summary:
{
"nvidia/nvidia-nemotron-nano-9b-v2": {
"token_usage": {
"prompt_tokens": 2581,
"completion_tokens": 15954,
"total_tokens": 18535
},
"request_usage": {
"successful_requests": 20,
"failed_requests": 0,
"total_requests": 20
},
"tokens_per_second": 416,
"requests_per_minute": 26
}
}
[16:35:06] [INFO] ๐ Measuring dataset column statistics:
[16:35:06] [INFO] |-- ๐ฑ column: 'diagnosis'
[16:35:06] [INFO] |-- ๐ฑ column: 'patient_summary'
[16:35:06] [INFO] |-- ๐ฒ column: 'patient_sampler'
[16:35:06] [INFO] |-- ๐ฒ column: 'doctor_sampler'
[16:35:06] [INFO] |-- ๐ฒ column: 'patient_id'
[16:35:06] [INFO] |-- ๐งฉ column: 'first_name'
[16:35:06] [INFO] |-- ๐งฉ column: 'last_name'
[16:35:06] [INFO] |-- ๐งฉ column: 'dob'
[16:35:06] [INFO] |-- ๐ฒ column: 'symptom_onset_date'
[16:35:06] [INFO] |-- ๐ฒ column: 'date_of_visit'
[16:35:06] [INFO] |-- ๐งฉ column: 'physician'
[16:35:06] [INFO] |-- ๐ column: 'physician_notes'
Inย [12]:
Copied!
# Load the generated dataset as a pandas DataFrame.
dataset = job_results.load_dataset()
dataset.head()
# Load the generated dataset as a pandas DataFrame.
dataset = job_results.load_dataset()
dataset.head()
Out[12]:
| diagnosis | patient_summary | patient_sampler | doctor_sampler | patient_id | symptom_onset_date | date_of_visit | first_name | last_name | dob | physician | physician_notes | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | cervical spondylosis | I've been having a lot of pain in my neck and ... | {'age': 77, 'bachelors_field': 'no_degree', 'b... | {'age': 80, 'bachelors_field': 'no_degree', 'b... | PT-9B5AA9F0 | 2024-11-12 | 2024-11-21 | Joseph | Mcconnell | 1948-09-04 | Dr. Odonnell | **Dr. Lori Odonnell, MD** **Primary Care Phy... |
| 1 | impetigo | I have a rash on my face that is getting worse... | {'age': 18, 'bachelors_field': 'stem', 'birth_... | {'age': 28, 'bachelors_field': 'no_degree', 'b... | PT-879882E0 | 2024-08-01 | 2024-08-30 | Ann | Thomas | 2007-09-30 | Dr. Thomas | **Dr. Melissa Thomas** **Primary Care Physic... |
| 2 | urinary tract infection | I have been urinating blood. I sometimes feel ... | {'age': 35, 'bachelors_field': 'no_degree', 'b... | {'age': 79, 'bachelors_field': 'education', 'b... | PT-C8FAA660 | 2024-11-09 | 2024-11-24 | Dalton | Phillips | 1990-01-31 | Dr. Johns | **Dr. Samantha Johns** **Primary Care Physic... |
| 3 | arthritis | I have been having trouble with my muscles and... | {'age': 63, 'bachelors_field': 'stem_related',... | {'age': 110, 'bachelors_field': 'no_degree', '... | PT-ED015BD6 | 2024-06-08 | 2024-06-30 | William | Price | 1962-09-19 | Dr. Smith | **Dr. Leah Smith, Primary Care Physician** *... |
| 4 | dengue | I have been feeling really sick. My body hurts... | {'age': 94, 'bachelors_field': 'no_degree', 'b... | {'age': 29, 'bachelors_field': 'no_degree', 'b... | PT-0F6852CC | 2024-11-09 | 2024-12-06 | Ashley | Perez | 1931-07-18 | Dr. Koch | **Dr. Michael Koch** **Primary Care Physicia... |
Inย [13]:
Copied!
# Load the analysis results into memory.
analysis = job_results.load_analysis()
analysis.to_report()
# Load the analysis results into memory.
analysis = job_results.load_analysis()
analysis.to_report()
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ ๐จ Data Designer Dataset Profile โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ Dataset Overview โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โ number of records โ number of columns โ percent complete records โ โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ โ 20 โ 12 โ 100.0% โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ ๐ฑ Seed-Dataset Columns โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โ column name โ data type โ number unique values โ โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ โ diagnosis โ string โ 12 (60.0%) โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ patient_summary โ string โ 20 (100.0%) โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ ๐ฒ Sampler Columns โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โ column name โ data type โ number unique values โ sampler type โ โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ โ patient_sampler โ dict โ 20 (100.0%) โ person_from_faker โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ doctor_sampler โ dict โ 20 (100.0%) โ person_from_faker โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ patient_id โ string โ 20 (100.0%) โ uuid โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ symptom_onset_date โ string โ 19 (95.0%) โ datetime โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ date_of_visit โ string โ 19 (95.0%) โ timedelta โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ ๐ LLM-Text Columns โโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโ โ โ โ โ prompt tokens โ completion tokens โ โ column name โ data type โ number unique values โ per record โ per record โ โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ โ physician_notes โ string โ 20 (100.0%) โ 111.0 +/- 9.0 โ 760.0 +/- 111.1 โ โโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโ ๐งฉ Expression Columns โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โ column name โ data type โ number unique values โ โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ โ first_name โ string โ 19 (95.0%) โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ last_name โ string โ 19 (95.0%) โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ dob โ string โ 20 (100.0%) โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค โ physician โ string โ 20 (100.0%) โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โญโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ Table Notes โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฎ โ โ โ 1. All token statistics are based on a sample of max(1000, len(dataset)) records. โ โ 2. Tokens are calculated using tiktoken's cl100k_base tokenizer. โ โ โ โฐโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฏ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
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