Update README.md

README.md

@@ -13,12 +13,28 @@ pretty_name: fineweb-edu-lance
 size_categories:
 - 1B<n<10B
 ---
+
+<center>
+    <img src="https://cdn-uploads.huggingface.co/production/uploads/61c141342aac764ce1654e43/wwRnEQydH9qdRtFofIE-A.png" alt="FineWeb-Edu: The finest collection of educational content the web has to offer">
+</center>
+
 # FineWeb-Edu (Lance Format)
 
-FineWeb-edu dataset with over 1.5 billion rows. Each passage ships with cleaned text, metadata, and 384-dim text embeddings for retrieval-heavy workloads.
+FineWeb-edu dataset consists of over 1.5 billion rows of educational web pages filtered from the FineWeb dataset.
+Each passage ships with cleaned text, metadata, and 384-dim text embeddings for retrieval-heavy workloads.
+
+## Why Lance?
+
+Lance is an open-source format designed for multimodal AI data, offering significant advantages over traditional formats for modern AI workloads.
+
+- **Blazing Fast Random Access**: Optimized for fetching scattered rows, making it ideal for random sampling, real-time ML serving, and interactive applications without performance degradation.
+- **Native Multimodal Support**: Store text, embeddings, and other data types together in a single file. Large binary objects are loaded lazily, and vectors are optimized for fast similarity search.
+- **Efficient Data Evolution**: Add new columns and backfill data without rewriting the entire dataset. This is perfect for evolving ML features, adding new embeddings, or introducing moderation tags over time.
+- **Versatile Querying**: Supports combining vector similarity search, full-text search, and SQL-style filtering in a single query, accelerated by on-disk indexes.
 
+## Quick Start
 
-## Load via `datasets.load_dataset`
+### Load with `datasets.load_dataset`
 
 ```python
 import datasets
@@ -33,6 +49,8 @@ for row in hf_ds.take(3):
     print(row["title"])
 ```
 
+### Load with Lance
+
 Use Lance's native connector when you need ANN search, FTS, or direct access to embeddings while still pointing to the copy hosted on Hugging Face:
 
 ```python
@@ -41,7 +59,10 @@ import lance
 ds = lance.dataset("hf://datasets/lance-format/fineweb-edu/data/train.lance")print(f"Total passages: {ds.count_rows():,}")
 ```
 
-These tables can also be consumed by [LanceDB](https://lancedb.github.io/lancedb/), the serverless vector database built on Lance, for simplified vector search and other queries.
+### Load with LanceDB
+
+These tables can also be consumed by [LanceDB](https://docs.lancedb.com/), the multimodal lakehouse for AI (built on top of Lance).
+LanceDB provides several convenience APIs for search, index creation and data updates on top of the Lance format.
 
 ```python
 import lancedb