Embeddings

Automatically generate embeddings for text, images, and structured data using pre-trained models.

Key Capabilities

Pre-trained models for common use cases
Batch processing for efficiency
Automatic handling of tokenization and preprocessing
Support for custom models

What is an Embedding?

Embeddings are vector representations of data. Embeddings are everywhere in modern deep learning, such as transformers, recommendation engines, layers of deep neural networks, encoders, and decoders.

Why Embeddings for Analyzing Deep Learning Models?

Data drift in unstructured data like images is complicated to measure. The measures typically used for drift in structured data do not extend to unstructured data. The general challenge with measuring unstructured data drift is that you need to understand the change in relationships inside the unstructured data itself. Embeddings are needed for users to access Arize’s UMAP product line.

Quick Start

import pandas as pd
from arize.embeddings import EmbeddingGenerator, UseCases

# List available models
print(EmbeddingGenerator.list_pretrained_models())

# Create example data
df = pd.DataFrame({
    "text": [
        "The product quality is excellent.",
        "Shipping was delayed by 3 days.",
        "Customer service was very helpful.",
    ],
})

# Generate embeddings for NLP
generator = EmbeddingGenerator.from_use_case(
    use_case=UseCases.NLP.SEQUENCE_CLASSIFICATION,
    model_name="distilbert-base-uncased",
    tokenizer_max_length=512,
    batch_size=100,
)

df["text_vector"] = generator.generate_embeddings(text_col=df["text"])

Supported Use Cases

Use Case	Model Types
`UseCases.NLP.SEQUENCE_CLASSIFICATION`	BERT, DistilBERT, RoBERTa
`UseCases.NLP.SUMMARIZATION`	BART, T5, Pegasus
`UseCases.CV.IMAGE_CLASSIFICATION`	ResNet, VGG, EfficientNet
`UseCases.CV.OBJECT_DETECTION`	YOLO, Faster R-CNN
`UseCases.STRUCTURED.TABULAR_EMBEDDINGS`	Custom tabular encoders

API reference

API clients

Key Capabilities

What is an Embedding?

Why Embeddings for Analyzing Deep Learning Models?

Quick Start

Supported Use Cases

​Key Capabilities

​What is an Embedding?

​Why Embeddings for Analyzing Deep Learning Models?

​Quick Start

​Supported Use Cases

Key Capabilities

What is an Embedding?

Why Embeddings for Analyzing Deep Learning Models?

Quick Start

Supported Use Cases