Generate LLM Embeddings On Your Local Machine

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In this video today we learn how to generate LLM embeddings using LLaMa 2 locally on our system.

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i just love how diverse your videos are ! even when i don't particulary look for something your videos drives me to learn more. thanks ❤

moumniable

Not bad, but if i may say any tip, i would say to use a sentence-transformer from hugging face for embeddings and then use a llama like llm only to customize the answer, because models created just for embeddings seems to be more accurate for this task. Also, langchain module is easier and useful than using numpy and requests, with lot more features. I use this setup most for RAG and seems to work pretty well.

rons

Powerful video! Guys, anyone knows how I can generate these embeddings if I were to deploy my app remotely?

Darkev

that's very interesting! I imagine you can build your local knowledge base in this way...
I need to make one for code-snippets that store knowledge bits find around....
Is `d` dimension fixed by the model? does it mean I have 4096 bytes to store my embedding?

EliSpizzichino

if you do it in Colab what url do you use?

JuanDiegoSalamanca-oyxs

Great video! But where comes faiss into play?

ddschaefer

I tried this with LLAMA3 8b locally. It can work if the sentences are short enough. But when I started plugins in long paragraphs (youtube transcripts) it becomes basically useless. Transformers that are creating for embedding (BERT for example) seems to work better. They also have lower computational cost compared to LLAMA. I tried again with and it works much better.

peterparker

First comment ❤ and ur videos are fantastic

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Generate LLM Embeddings On Your Local Machine

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