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 ❤
@rons968 ай бұрын
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.
@henrischomacker60977 ай бұрын
Very interesting hint. Why would you suggest to use a sentence-transformer from hugging face for creating the embeddings instead? Which method does a sentence-transformer from hugging face use to create the embeddings and which one does ollama use?
@hackdonalds7 ай бұрын
I tried llama2 and mistral embeddings through ollama embeddings api. The similarity search results were sht compared to Xenova/all-MiniLM-L6-v2 or gte-small
@rons965 ай бұрын
@@hackdonalds yes, llama for embeddings is not good, with sentence-transformers i mean that one you mentioned, then use llama to elaborate the sentence. There's another model better for embeddings but it will require more resources and i don't remember the name now.
@rahulmakwana66318 күн бұрын
@@rons96instructorembedding
@godwinntowdanso41112 ай бұрын
Spot on. Simplified presentation
@user-td4pf6rr2t2 ай бұрын
Cool guide. Very well explained. +1
@mohammadalibazyar50796 ай бұрын
thanks, bro... really helpful ❤
@Darkev777 ай бұрын
Powerful video! Guys, anyone knows how I can generate these embeddings if I were to deploy my app remotely?
@iamreallybadatphysicsbutda81988 ай бұрын
Great video! 😃
@EliSpizzichino6 ай бұрын
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?
@dangalimov74358 ай бұрын
Brilliant!
@ddschaefer8 ай бұрын
Great video! But where comes faiss into play?
@peterparker51614 ай бұрын
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 "nomic-embed-text-v1.f16.gguf" and it works much better.