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[
"Quantized Emdedding Models - Qdrant",
"Transcript:"
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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(27) | [
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"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(27) | [
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[
"Quantized Emdedding Models - Qdrant",
"Transcript:"
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] | p | And that is why Fast Embed is very light. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,375 |
[
"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(27) | [
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"tags",
"tags/quantized-emdedding-models"
] | 16,376 |
[
"Quantized Emdedding Models - Qdrant",
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] | /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(27) | [
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"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(27) | [
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] | p | Right? | [
"tags",
"tags/quantized-emdedding-models"
] | 16,378 |
[
"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(27) | [
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[
"Quantized Emdedding Models - Qdrant",
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[
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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(27) | [
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[
"Quantized Emdedding Models - Qdrant",
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"tags",
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[
"Quantized Emdedding Models - Qdrant",
"Transcript:"
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[
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"tags",
"tags/quantized-emdedding-models"
] | 16,386 |
[
"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(29) | [
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[
"Quantized Emdedding Models - Qdrant",
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[
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] | p | So I’m just warning you. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,391 |
[
"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(30) | [
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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(31) | [
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[
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"tags",
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] | 16,394 |
[
"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(31) | [
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] | p | We would love to do that. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,395 |
[
"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(31) | [
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] | p | If there’s specific model within those, let’s say you want Clip or Seglip or a specific audio model, please mention that either on that discord or our GitHub so that we can plan accordingly. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,396 |
[
"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(31) | [
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] | p | So yeah, that’s the idea. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,397 |
[
"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(31) | [
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"tags",
"tags/quantized-emdedding-models"
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[
"Quantized Emdedding Models - Qdrant",
"Transcript:"
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] | p | We don’t want to have too many models because then that creates confusion for our end users and that is why we take opinated stance and that is actually a good segue. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,399 |
[
"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(31) | [
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[
"Quantized Emdedding Models - Qdrant",
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] | /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(31) | [
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[
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] | p | So this is a very Linux way of saying that we do one thing and we try to do that one thing really well. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,402 |
[
"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(32) | [
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"Quantized Emdedding Models - Qdrant",
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[
"Quantized Emdedding Models - Qdrant",
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[
"Quantized Emdedding Models - Qdrant",
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] | /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(32) | [
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[
"Quantized Emdedding Models - Qdrant",
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[
"Quantized Emdedding Models - Qdrant",
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] | p | You could even see a very familiar integration which is let’s say langchain. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,408 |
[
"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(32) | [
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] | p | I think most people here would have looked at this in some shape or form earlier. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,409 |
[
"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(32) | [
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] | p | This is also very familiar and very straightforward. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,410 |
[
"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(32) | [
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"tags",
"tags/quantized-emdedding-models"
] | 16,413 |
[
"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(33) | [
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] | p | You will notice that we have a passage and query keys here which means that our retrieval model which we have used as default here, takes these into account that if there is a passage and a query they need to be mapped together and a question and answer context is captured in the model training itself. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,414 |
[
"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(33) | [
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] | p | The other caveat is that we pass on the token limits or context windows from the embedding model creators themselves. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,415 |
[
"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(33) | [
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] | p | So in the case of this model, which is BGE base, that is 512 BGE tokens. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,416 |
[
"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(34) | [
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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(34) | [
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] | p | One thing on this, we had Neil’s from Cohere on last week and he was talking about Cohere’s embed version three, I think, or V three, he was calling it. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,418 |
[
"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(34) | [
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"tags",
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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(34) | [
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[
"Quantized Emdedding Models - Qdrant",
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[
"Quantized Emdedding Models - Qdrant",
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[
"Quantized Emdedding Models - Qdrant",
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"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(35) | [
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"tags",
"tags/quantized-emdedding-models"
] | 16,424 |
[
"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(35) | [
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"tags",
"tags/quantized-emdedding-models"
] | 16,425 |
[
"Quantized Emdedding Models - Qdrant",
"Transcript:"
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] | p | So that’s perfectly fair. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,426 |
[
"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(35) | [
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"tags",
"tags/quantized-emdedding-models"
] | 16,427 |
[
"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(35) | [
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] | p | Also, I think Nils called out that coherent embed V three is compatible with binary quantization. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,428 |
[
"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(35) | [
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"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(36) | [
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[
"Quantized Emdedding Models - Qdrant",
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] | p | Okay, we are binary quantization aware and they’ve been trained for it. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,431 |
[
"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(36) | [
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"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(36) | [
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"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(36) | [
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] | p | So please of that might be worth it because it saves about 30 x in memory costs. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,434 |
[
"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(36) | [
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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(37) | [
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[
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] | p | All right, so behind the scenes, I think this is my favorite part of this. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,439 |
[
"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(38) | [
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] | p | It’s also very short. | [
"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(38) | [
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"tags",
"tags/quantized-emdedding-models"
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[
"Quantized Emdedding Models - Qdrant",
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] | /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(38) | [
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"tags",
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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(38) | [
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[
"Quantized Emdedding Models - Qdrant",
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[
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] | p | We also want to support GPUs. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,445 |
[
"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(38) | [
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] | p | We had some configuration issues on different Nvidia configurations. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,446 |
[
"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(38) | [
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[
"Quantized Emdedding Models - Qdrant",
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"tags",
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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(39) | [
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"tags",
"tags/quantized-emdedding-models"
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[
"Quantized Emdedding Models - Qdrant",
"Transcript:"
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] | p | But you can pass that. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,450 |
[
"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(39) | [
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[
"Quantized Emdedding Models - Qdrant",
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] | /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(39) | [
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[
"Quantized Emdedding Models - Qdrant",
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] | p | And we quantize the models for you. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,453 |
[
"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(39) | [
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] | p | So when we quantize, what it means is we do a bunch of tricks supported by a huge shout out to hugging faces optimum. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,454 |
[
"Quantized Emdedding Models - Qdrant",
"Transcript:"
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"tags",
"tags/quantized-emdedding-models"
] | 16,455 |
[
"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(39) | [
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"tags",
"tags/quantized-emdedding-models"
] | 16,456 |
[
"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(40) | [
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"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(40) | [
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"tags",
"tags/quantized-emdedding-models"
] | 16,458 |
[
"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(40) | [
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"tags",
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[
"Quantized Emdedding Models - Qdrant",
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"tags/quantized-emdedding-models"
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[
"Quantized Emdedding Models - Qdrant",
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] | p | Yeah, that’s about it. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,461 |
[
"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(40) | [
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] | p | Those are the two things which we do from which we get bulk of these speed gains. | [
"tags",
"tags/quantized-emdedding-models"
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[
"Quantized Emdedding Models - Qdrant",
"Transcript:"
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] | p | And I think this goes back to the question which you opened with. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,463 |
[
"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(40) | [
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] | p | Yes, we do want to support multimodal. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,464 |
[
"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(40) | [
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] | p | We are looking at how we can do an on and export of Clip, which is as robust as Clip. | [
"tags",
"tags/quantized-emdedding-models"
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[
"Quantized Emdedding Models - Qdrant",
"Transcript:"
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[
"Quantized Emdedding Models - Qdrant",
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"tags",
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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(41) | [
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"tags",
"tags/quantized-emdedding-models"
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[
"Quantized Emdedding Models - Qdrant",
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"tags",
"tags/quantized-emdedding-models"
] | 16,469 |
[
"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(41) | [
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"tags",
"tags/quantized-emdedding-models"
] | 16,470 |
[
"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(41) | [
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] | p | So we will do that soon. | [
"tags",
"tags/quantized-emdedding-models"
] | 16,471 |
Subsets and Splits