krzysztof/landing_page
1
0
Fork 0
mirror of https://github.com/qdrant/landing_page.git synced 2026-10-05 19:08:32 +02:00
Code Issues Packages Projects Releases Wiki Activity

Update fastembed-colbert.md

Browse Source
This commit is contained in:
Andrey Vasnetsov
2025-12-03 18:46:12 +01:00
committed by GitHub
parent 78d70516b6
commit c9a41c0b17
1 changed files with 2 additions and 2 deletions
Download Patch File Download Diff File Expand all files Collapse all files
qdrant-landing/content/documentation/fastembed/fastembed-colbert.md
+2 -2
View File
@@ -81,7 +81,7 @@ The model files will be fetched and downloaded, with progress showing.
We will vectorize a toy movie description dataset with ColBERT:
<details>
<summary> <span style="background-color: gray; color: black;"> Movie description dataset </span> </summary>
<summary> Movie description dataset </summary>
```python
descriptions = ["In 1431, Jeanne d'Arc is placed on trial on charges of heresy. The ecclesiastical jurists attempt to force Jeanne to recant her claims of holy visions.",
@@ -166,7 +166,7 @@ qdrant_client.create_collection(
To make this collection human-readable, let's save movie metadata (name, description in text form and movie's length) together with an embedded description.
<details>
<summary> <span style="background-color: gray; color: black;"> Movie metadata </span> </summary>
<summary> Movie metadata </summary>
```python
metadata = [{"movie_name": "The Passion of Joan of Arc", "movie_watch_time_min": 114, "movie_description": "In 1431, Jeanne d'Arc is placed on trial on charges of heresy. The ecclesiastical jurists attempt to force Jeanne to recant her claims of holy visions."},