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[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(70)
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[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(70)
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p
Got into the weeds of retrieval there.
[ "blog", "blog/fast-embed-models" ]
16,173
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(70)
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p
Sorry.
[ "blog", "blog/fast-embed-models" ]
16,174
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(71)
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p
Demetrios:
[ "blog", "blog/fast-embed-models" ]
16,175
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(71)
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p
I like it though.
[ "blog", "blog/fast-embed-models" ]
16,176
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(71)
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p
I appreciate it.
[ "blog", "blog/fast-embed-models" ]
16,177
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(71)
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p
So what about when it comes to the know, we had Andre V, the CTO of Qdrant on here a few weeks ago.
[ "blog", "blog/fast-embed-models" ]
16,178
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(71)
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p
He was talking about binary quantization.
[ "blog", "blog/fast-embed-models" ]
16,179
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(71)
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p
But then when it comes to quantizing embedding models, in the docs you mentioned like quantized embedding models for fast CPU generation.
[ "blog", "blog/fast-embed-models" ]
16,180
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(71)
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p
Can you explain a little bit more about what quantized embedding models are and how they enhance the CPU performance?
[ "blog", "blog/fast-embed-models" ]
16,181
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(72)
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p
Nirant Kasliwal:
[ "blog", "blog/fast-embed-models" ]
16,182
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(72)
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p
So it’s a shorthand to say that they optimize CPU performance.
[ "blog", "blog/fast-embed-models" ]
16,183
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(72)
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p
I think the more correct way to look at it is that we use the CPU better.
[ "blog", "blog/fast-embed-models" ]
16,184
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(72)
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p
But let’s talk about optimization or quantization, which we do here, right?
[ "blog", "blog/fast-embed-models" ]
16,185
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(72)
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p
So most of what we do is from optimum and the way optimum call set up is they call these levels.
[ "blog", "blog/fast-embed-models" ]
16,186
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(72)
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p
So you can basically go from let’s say level zero, which is there are no optimizations to let’s say 99 where there’s a bunch of extra optimizations happening.
[ "blog", "blog/fast-embed-models" ]
16,187
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(72)
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p
And these are different flags which you can switch.
[ "blog", "blog/fast-embed-models" ]
16,188
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(72)
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p
And here are some examples which I remember.
[ "blog", "blog/fast-embed-models" ]
16,189
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(72)
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p
So for instance, there is a norm layer which you can fuse with the previous operation.
[ "blog", "blog/fast-embed-models" ]
16,190
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(72)
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p
Then there are different attention layers which you can fuse with the previous one because you’re not going to update them anymore, right?
[ "blog", "blog/fast-embed-models" ]
16,191
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(72)
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p
So what we do in training is we update them.
[ "blog", "blog/fast-embed-models" ]
16,192
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(73)
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p
Nirant Kasliwal:
[ "blog", "blog/fast-embed-models" ]
16,193
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(73)
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p
You know that you’re not going to update them because you’re using them for inference.
[ "blog", "blog/fast-embed-models" ]
16,194
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(73)
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p
So let’s say when somebody asks a question, you want that to be converted into an embedding as fast as possible and as cheaply as possible.
[ "blog", "blog/fast-embed-models" ]
16,195
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(73)
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p
So you can discard all these extra information which you are most likely to not going to use.
[ "blog", "blog/fast-embed-models" ]
16,196
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(73)
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p
So there’s a bunch of those things and obviously you can use mixed precision, which most people have heard of with projects, let’s say like lounge CPP that you can use FP 16 mixed precision or a bunch of these things.
[ "blog", "blog/fast-embed-models" ]
16,197
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(73)
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p
Let’s say if you are doing GPU only.
[ "blog", "blog/fast-embed-models" ]
16,198
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(73)
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p
So some of these things like FP 16 work better on GPU.
[ "blog", "blog/fast-embed-models" ]
16,199
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(73)
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p
The CPU part of that claim comes from how ONNX the runtime which we use allows you to optimize whatever CPU instruction set you are using.
[ "blog", "blog/fast-embed-models" ]
16,200
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(73)
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p
So as an example with intel you can say, okay, I’m going to use the Vino instruction set or the optimization.
[ "blog", "blog/fast-embed-models" ]
16,201
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(74)
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p
Nirant Kasliwal:
[ "blog", "blog/fast-embed-models" ]
16,202
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(74)
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p
So when we do quantize it, we do quantization right now with CPUs in mind.
[ "blog", "blog/fast-embed-models" ]
16,203
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(74)
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p
So what we would want to do at some point in the future is give you a GPU friendly quantized model and we can do a device check and say, okay, we can see that a GPU is available and download the GPU friendly model first for you.
[ "blog", "blog/fast-embed-models" ]
16,204
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(74)
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p
Awesome.
[ "blog", "blog/fast-embed-models" ]
16,205
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(74)
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p
Does that answer the.
[ "blog", "blog/fast-embed-models" ]
16,206
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(74)
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p
Question.
[ "blog", "blog/fast-embed-models" ]
16,207
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(75)
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p
Demetrios:
[ "blog", "blog/fast-embed-models" ]
16,208
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(75)
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p
I mean, for me, yeah, but we’ll see what the chat says.
[ "blog", "blog/fast-embed-models" ]
16,209
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(76)
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p
Nirant Kasliwal:
[ "blog", "blog/fast-embed-models" ]
16,210
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(76)
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p
Yes, let’s do that.
[ "blog", "blog/fast-embed-models" ]
16,211
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(77)
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p
Demetrios:
[ "blog", "blog/fast-embed-models" ]
16,212
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(77)
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p
What everybody says there.
[ "blog", "blog/fast-embed-models" ]
16,213
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(77)
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p
Dude, this has been great.
[ "blog", "blog/fast-embed-models" ]
16,214
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(77)
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p
I really appreciate you coming and walking through everything we need to know, not only about fast embed, but I think about embeddings in general.
[ "blog", "blog/fast-embed-models" ]
16,215
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(77)
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p
All right, I will see you later.
[ "blog", "blog/fast-embed-models" ]
16,216
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(77)
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p
Thank you so much, Naran.
[ "blog", "blog/fast-embed-models" ]
16,217
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(77)
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p
Thank you, everyone, for coming out.
[ "blog", "blog/fast-embed-models" ]
16,218
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(77)
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p
If you want to present, please let us know.
[ "blog", "blog/fast-embed-models" ]
16,219
[ "FastEmbed: Fast & Lightweight Embedding Generation - Nirant Kasliwal | Vector Space Talks - Qdrant", "Transcript:" ]
/blog/fast-embed-models/
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(77)
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p
Hit us up, because we would love to have you at our vector space talks.
[ "blog", "blog/fast-embed-models" ]
16,220
[ "Quantized Emdedding Models - Qdrant" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > blockquote:nth-of-type(1) > p
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p
“When things are actually similar or how we define similarity.
[ "tags", "tags/quantized-emdedding-models" ]
16,221
[ "Quantized Emdedding Models - Qdrant" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > blockquote:nth-of-type(1) > p
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p
They are close to each other and if they are not, they’re far from each other.
[ "tags", "tags/quantized-emdedding-models" ]
16,222
[ "Quantized Emdedding Models - Qdrant" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > blockquote:nth-of-type(1) > p
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p
This is what a model or embedding model tries to do.”–
[ "tags", "tags/quantized-emdedding-models" ]
16,223
[ "Quantized Emdedding Models - Qdrant" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > blockquote:nth-of-type(1) > p
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p
Nirant Kasliwal
[ "tags", "tags/quantized-emdedding-models" ]
16,224
[ "Quantized Emdedding Models - Qdrant" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(1)
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p
Heard about FastEmbed?
[ "tags", "tags/quantized-emdedding-models" ]
16,225
[ "Quantized Emdedding Models - Qdrant" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(1)
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p
It’s a game-changer.
[ "tags", "tags/quantized-emdedding-models" ]
16,226
[ "Quantized Emdedding Models - Qdrant" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(1)
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p
Nirant shares tricks on how to improve your embedding models.
[ "tags", "tags/quantized-emdedding-models" ]
16,227
[ "Quantized Emdedding Models - Qdrant" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(1)
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p
You might want to give it a shot!
[ "tags", "tags/quantized-emdedding-models" ]
16,228
[ "Quantized Emdedding Models - Qdrant" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(2)
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p
Nirant Kasliwal, the creator and maintainer of FastEmbed, has made notable contributions to the Finetuning Cookbook at OpenAI Cookbook.
[ "tags", "tags/quantized-emdedding-models" ]
16,229
[ "Quantized Emdedding Models - Qdrant" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(2)
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p
His contributions extend to the field of Natural Language Processing (NLP), with over 5,000 copies of the NLP book sold.
[ "tags", "tags/quantized-emdedding-models" ]
16,230
[ "Quantized Emdedding Models - Qdrant" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(3)
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p
Listen to the episode on Spotify, Apple Podcast, Podcast addicts, Castbox.
[ "tags", "tags/quantized-emdedding-models" ]
16,231
[ "Quantized Emdedding Models - Qdrant" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(3)
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p
You can also watch this episode on YouTube.
[ "tags", "tags/quantized-emdedding-models" ]
16,232
[ "Quantized Emdedding Models - Qdrant" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > h2:nth-of-type(1)
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h2
Top Takeaways:
[ "tags", "tags/quantized-emdedding-models" ]
16,233
[ "Quantized Emdedding Models - Qdrant", "Top Takeaways:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(4)
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p
Nirant Kasliwal, AI Engineer at Qdrant joins us on Vector Space Talks to dive into FastEmbed, a lightning-quick method for generating embeddings.
[ "tags", "tags/quantized-emdedding-models" ]
16,234
[ "Quantized Emdedding Models - Qdrant", "Top Takeaways:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(5)
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p
In this episode, Nirant shares insights, tips, and innovative ways to enhance embedding generation.
[ "tags", "tags/quantized-emdedding-models" ]
16,235
[ "Quantized Emdedding Models - Qdrant", "Top Takeaways:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(6)
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p
5 Keys to Learning from the Episode:
[ "tags", "tags/quantized-emdedding-models" ]
16,236
[ "Quantized Emdedding Models - Qdrant", "Top Takeaways:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > ol > li:nth-of-type(1)
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li
Nirant introduces some hacker tricks for improving embedding models - you won’t want to miss these!
[ "tags", "tags/quantized-emdedding-models" ]
16,237
[ "Quantized Emdedding Models - Qdrant", "Top Takeaways:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > ol > li:nth-of-type(2)
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li
Learn how quantized embedding models can enhance CPU performance.
[ "tags", "tags/quantized-emdedding-models" ]
16,238
[ "Quantized Emdedding Models - Qdrant", "Top Takeaways:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > ol > li:nth-of-type(3)
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li
Get an insight into future plans for GPU-friendly quantized models.
[ "tags", "tags/quantized-emdedding-models" ]
16,239
[ "Quantized Emdedding Models - Qdrant", "Top Takeaways:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > ol > li:nth-of-type(4)
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li
Understand how to select default models in Qdrant based on MTEB benchmark, and how to calibrate them for domain-specific tasks.
[ "tags", "tags/quantized-emdedding-models" ]
16,240
[ "Quantized Emdedding Models - Qdrant", "Top Takeaways:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > ol > li:nth-of-type(5)
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li
Find out how Fast Embed, a Python library created by Nirant, can solve common challenges in embedding creation and enhance the speed and efficiency of your workloads.
[ "tags", "tags/quantized-emdedding-models" ]
16,241
[ "Quantized Emdedding Models - Qdrant", "Top Takeaways:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > blockquote:nth-of-type(2) > p
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p
Fun Fact: The largest header or adapter used in production is only about 400-500 KBs – proof that bigger doesn’t always mean better!
[ "tags", "tags/quantized-emdedding-models" ]
16,242
[ "Quantized Emdedding Models - Qdrant" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > h2:nth-of-type(2)
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h2
Show Notes:
[ "tags", "tags/quantized-emdedding-models" ]
16,243
[ "Quantized Emdedding Models - Qdrant", "Show Notes:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(7)
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p
00:00 Nirant discusses FastEmbed at Vector Space Talks.05:00 Tokens are expensive and slow in open air.08:40 FastEmbed is fast and lightweight.09:49 Supporting multimodal embedding is our plan.15:21 No findings.
[ "tags", "tags/quantized-emdedding-models" ]
16,244
[ "Quantized Emdedding Models - Qdrant", "Show Notes:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(7)
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p
Enhancing model downloads and performance.16:59 Embed creation on your own compute, not cloud.
[ "tags", "tags/quantized-emdedding-models" ]
16,245
[ "Quantized Emdedding Models - Qdrant", "Show Notes:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(7)
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p
Control and simplicity are prioritized.21:06 Qdrant is fast for embedding similarity search.24:07 Engineer’s mindset: make informed guesses, set budgets.26:11 Optimize embeddings with questions and linear layers.29:55 Fast, cheap inference using mixed precision embeddings.
[ "tags", "tags/quantized-emdedding-models" ]
16,246
[ "Quantized Emdedding Models - Qdrant" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > h2:nth-of-type(3)
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h2
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html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(8)
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p
“There is the academic way of looking at and then there is the engineer way of looking at it, and then there is the hacker way of looking at it.
[ "tags", "tags/quantized-emdedding-models" ]
16,248
[ "Quantized Emdedding Models - Qdrant", "More Quotes from Nirant:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(8)
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p
And I will give you all these three answers in that order.”–
[ "tags", "tags/quantized-emdedding-models" ]
16,249
[ "Quantized Emdedding Models - Qdrant", "More Quotes from Nirant:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(8)
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p
Nirant Kasliwal
[ "tags", "tags/quantized-emdedding-models" ]
16,250
[ "Quantized Emdedding Models - Qdrant", "More Quotes from Nirant:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(9)
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p
“The engineer’s mindset now tells you that the best way to build something is to make an informed guess about what workload or challenges you’re going to foresee.
[ "tags", "tags/quantized-emdedding-models" ]
16,251
[ "Quantized Emdedding Models - Qdrant", "More Quotes from Nirant:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(9)
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p
Right.
[ "tags", "tags/quantized-emdedding-models" ]
16,252
[ "Quantized Emdedding Models - Qdrant", "More Quotes from Nirant:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(9)
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p
Like a civil engineer builds a bridge around how many cars they expect, they’re obviously not going to build a bridge to carry a shipload, for instance, or a plane load, which are very different.”–
[ "tags", "tags/quantized-emdedding-models" ]
16,253
[ "Quantized Emdedding Models - Qdrant", "More Quotes from Nirant:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(9)
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p
Nirant Kasliwal
[ "tags", "tags/quantized-emdedding-models" ]
16,254
[ "Quantized Emdedding Models - Qdrant", "More Quotes from Nirant:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(10)
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p
“I think the more correct way to look at it is that we use the CPU better.”–
[ "tags", "tags/quantized-emdedding-models" ]
16,255
[ "Quantized Emdedding Models - Qdrant", "More Quotes from Nirant:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(10)
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p
Nirant Kasliwal
[ "tags", "tags/quantized-emdedding-models" ]
16,256
[ "Quantized Emdedding Models - Qdrant" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > h2:nth-of-type(4)
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h2
Transcript:
[ "tags", "tags/quantized-emdedding-models" ]
16,257
[ "Quantized Emdedding Models - Qdrant", "Transcript:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(11)
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Demetrios:
[ "tags", "tags/quantized-emdedding-models" ]
16,258
[ "Quantized Emdedding Models - Qdrant", "Transcript:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(11)
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Welcome back, everyone, to another vector space talks.
[ "tags", "tags/quantized-emdedding-models" ]
16,259
[ "Quantized Emdedding Models - Qdrant", "Transcript:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(11)
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p
Today we’ve got my man Nirant coming to us talking about FastEmbed.
[ "tags", "tags/quantized-emdedding-models" ]
16,260
[ "Quantized Emdedding Models - Qdrant", "Transcript:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(11)
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p
For those, if this is your first time at our vector space talks, we like to showcase some of the cool stuff that the community in Qdrant is doing, the Qdrant community is doing.
[ "tags", "tags/quantized-emdedding-models" ]
16,261
[ "Quantized Emdedding Models - Qdrant", "Transcript:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(11)
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p
And we also like to show off some of the cool stuff that Qdrant itself is coming out with.
[ "tags", "tags/quantized-emdedding-models" ]
16,262
[ "Quantized Emdedding Models - Qdrant", "Transcript:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(11)
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p
And this is one of those times that we are showing off what Qdrant itself came out with with FastEmbed.
[ "tags", "tags/quantized-emdedding-models" ]
16,263
[ "Quantized Emdedding Models - Qdrant", "Transcript:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(11)
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p
And we’ve got my man Nirant around here somewhere.
[ "tags", "tags/quantized-emdedding-models" ]
16,264
[ "Quantized Emdedding Models - Qdrant", "Transcript:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(11)
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p
I am going to bring him on stage and I will welcome him by saying Nirant a little bit about his bio, we could say.
[ "tags", "tags/quantized-emdedding-models" ]
16,265
[ "Quantized Emdedding Models - Qdrant", "Transcript:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(11)
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p
So, Naran, what’s going on, dude?
[ "tags", "tags/quantized-emdedding-models" ]
16,266
[ "Quantized Emdedding Models - Qdrant", "Transcript:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(11)
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p
Let me introduce you real fast before we get cracking.
[ "tags", "tags/quantized-emdedding-models" ]
16,267
[ "Quantized Emdedding Models - Qdrant", "Transcript:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(12)
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Demetrios:
[ "tags", "tags/quantized-emdedding-models" ]
16,268
[ "Quantized Emdedding Models - Qdrant", "Transcript:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(12)
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And you are a man that wears many hats.
[ "tags", "tags/quantized-emdedding-models" ]
16,269
[ "Quantized Emdedding Models - Qdrant", "Transcript:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(12)
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p
You’re currently working on the Devrel team at Qdrant, right?
[ "tags", "tags/quantized-emdedding-models" ]
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[ "Quantized Emdedding Models - Qdrant", "Transcript:" ]
/tags/quantized-emdedding-models/
html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(12)
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p
I like that shirt that you got there.
[ "tags", "tags/quantized-emdedding-models" ]
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