metadata
task_categories:
- document-question-answering
- visual-document-retrieval
Contextualized Embeddings Benchmark
This repository contains evaluation code for the "Contextualized Embeddings" project.
Installation
pip install -e .
pip install git+https://github.com/jina-ai/late-chunking --no-deps # for late-chunking with jina
Usage
Refer to scripts/evaluation.py for an example of how to use the code.
from datasets import load_dataset
from cde_benchmark.embedders.sentence_transformer_embedder import SentenceTransformerEmbedder
from cde_benchmark.embedders.naive_contextual_embedder import NaiveContextualEmbedder
from cde_benchmark.formatters.data_formatter import DataFormatter
# Datasets should be correctly formatted
formatter = DataFormatter("illuin-cde/chunked-mldr", split="test")
# Non-nested example
embedder = SentenceTransformerEmbedder("intfloat/e5-base-v2")
metrics = embedder.compute_metrics_e2e(formatter)
print(metrics)
# Nested example (for conxtualized embeddings models)
embedder = NaiveContextualEmbedder("intfloat/e5-base-v2")
metrics = embedder.compute_metrics_e2e(formatter)
print(metrics)