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Remove placeholder video

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Kacper Łukawski
2026-01-02 11:18:01 +01:00
parent 561f93e480
commit 0b2fae05ea
13 changed files with 14 additions and 14 deletions
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qdrant-landing/content/course/multi-vector-search/module-1/late-interaction-basics.md
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@@ -16,7 +16,7 @@ This lesson introduces the late interaction paradigm - the foundation of multi-v
<div class="video">
<iframe
src="https://www.youtube.com/embed/dQw4w9WgXcQ"
src="https://www.youtube.com/embed/xK9mV7zR4pL"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
referrerpolicy="strict-origin-when-cross-origin"
qdrant-landing/content/course/multi-vector-search/module-1/maxsim-distance.md
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@@ -16,7 +16,7 @@ Understanding MaxSim is important for working with multi-vector search effective
<div class="video">
<iframe
src="https://www.youtube.com/embed/dQw4w9WgXcQ"
src="https://www.youtube.com/embed/xK9mV7zR4pL"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
referrerpolicy="strict-origin-when-cross-origin"
qdrant-landing/content/course/multi-vector-search/module-1/multi-vector-in-qdrant.md
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@@ -18,7 +18,7 @@ By the end, you'll understand the key configuration parameters, know when to use
<div class="video">
<iframe
src="https://www.youtube.com/embed/dQw4w9WgXcQ"
src="https://www.youtube.com/embed/xK9mV7zR4pL"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
referrerpolicy="strict-origin-when-cross-origin"
qdrant-landing/content/course/multi-vector-search/module-1/problems-multi-vector.md
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@@ -16,7 +16,7 @@ The good news: Module 3 covers optimization techniques that address many of thes
<div class="video">
<iframe
src="https://www.youtube.com/embed/dQw4w9WgXcQ"
src="https://www.youtube.com/embed/xK9mV7zR4pL"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
referrerpolicy="strict-origin-when-cross-origin"
qdrant-landing/content/course/multi-vector-search/module-1/use-cases-multi-vector.md
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@@ -16,7 +16,7 @@ The answer comes down to one core capability: **fine-grained matching**. In the
<div class="video">
<iframe
src="https://www.youtube.com/embed/dQw4w9WgXcQ"
src="https://www.youtube.com/embed/xK9mV7zR4pL"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
referrerpolicy="strict-origin-when-cross-origin"
qdrant-landing/content/course/multi-vector-search/module-2/colpali-family.md
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@@ -16,7 +16,7 @@ Let's explore what each model offers and when to use it.
<div class="video">
<iframe
src="https://www.youtube.com/embed/dQw4w9WgXcQ"
src="https://www.youtube.com/embed/xK9mV7zR4pL"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
referrerpolicy="strict-origin-when-cross-origin"
qdrant-landing/content/course/multi-vector-search/module-2/how-colpali-works.md
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@@ -16,7 +16,7 @@ Understanding ColPali's architecture helps you leverage its full potential for m
<div class="video">
<iframe
src="https://www.youtube.com/embed/dQw4w9WgXcQ"
src="https://www.youtube.com/embed/xK9mV7zR4pL"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
referrerpolicy="strict-origin-when-cross-origin"
@@ -92,7 +92,7 @@ For text inputs, there isn't any additional preprocessing step, but it is tokeni
Vision transformers, the foundation of ColPali, don't process entire images at once. Instead, they divide images into a grid of fixed-size patches - think of it like a checkerboard overlaid on your document.
ColPali pipeline starts with a document. It is usually a screenshot of a single PDF page, or anything you want to encode. While you might convert a PDF page to a high-resolution screenshot to preserve visual details during conversion, **the ColPali preprocessing itself resizes images to a fixed resolution** of **448×448 pixels** before processing.
The ColPali pipeline starts with a document. It is usually a screenshot of a single PDF page, or anything you want to encode. While you might convert a PDF page to a high-resolution screenshot to preserve visual details during conversion, **the ColPali preprocessing itself resizes images to a fixed resolution** of **448×448 pixels** before processing.
This fixed-size input is then divided into patches:
- **Patch size**: 14×14 pixels per patch
qdrant-landing/content/course/multi-vector-search/module-2/visual-interpretability.md
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@@ -16,7 +16,7 @@ This transparency is invaluable for building trust in multi-modal search systems
<div class="video">
<iframe
src="https://www.youtube.com/embed/dQw4w9WgXcQ"
src="https://www.youtube.com/embed/xK9mV7zR4pL"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
referrerpolicy="strict-origin-when-cross-origin"
qdrant-landing/content/course/multi-vector-search/module-3/evaluating-pipelines.md
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@@ -16,7 +16,7 @@ This lesson provides a framework for making data-driven decisions about your mul
<div class="video">
<iframe
src="https://www.youtube.com/embed/dQw4w9WgXcQ"
src="https://www.youtube.com/embed/xK9mV7zR4pL"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
referrerpolicy="strict-origin-when-cross-origin"
qdrant-landing/content/course/multi-vector-search/module-3/multi-stage-retrieval.md
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@@ -16,7 +16,7 @@ Qdrant's Universal Query API makes it easy to build sophisticated multi-stage re
<div class="video">
<iframe
src="https://www.youtube.com/embed/dQw4w9WgXcQ"
src="https://www.youtube.com/embed/xK9mV7zR4pL"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
referrerpolicy="strict-origin-when-cross-origin"
qdrant-landing/content/course/multi-vector-search/module-3/muvera.md
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@@ -16,7 +16,7 @@ Understanding MUVERA is key to scaling multi-vector search to millions of docume
<div class="video">
<iframe
src="https://www.youtube.com/embed/dQw4w9WgXcQ"
src="https://www.youtube.com/embed/xK9mV7zR4pL"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
referrerpolicy="strict-origin-when-cross-origin"
qdrant-landing/content/course/multi-vector-search/module-3/pooling-techniques.md
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@@ -16,7 +16,7 @@ Pooling is particularly effective when combined with quantization for maximum me
<div class="video">
<iframe
src="https://www.youtube.com/embed/dQw4w9WgXcQ"
src="https://www.youtube.com/embed/xK9mV7zR4pL"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
referrerpolicy="strict-origin-when-cross-origin"
qdrant-landing/content/course/multi-vector-search/module-3/quantization-techniques.md
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@@ -16,7 +16,7 @@ Choosing the right quantization method depends on your quality requirements and
<div class="video">
<iframe
src="https://www.youtube.com/embed/dQw4w9WgXcQ"
src="https://www.youtube.com/embed/xK9mV7zR4pL"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
referrerpolicy="strict-origin-when-cross-origin"