GPT-3 Embeddings: Perform Text Similarity, Semantic Search, Classification, and Clustering | Code

Hands-on GPT-3 tutorial Learn How to use GPT-3 Embeddings to perform Text Similarity, Semantic Search, Classification, and Clustering.

Open AI claims its embeddings outperform top models in 3 standard benchmarks, including a 20% relative improvement in code search.

In the last video, we learn How to use Sentence Transformers to perform Sentence Embedding, Sentence Similarity, Semantic search, and Clustering.

NLP Beginner to Advanced Playlist:

I am a Freelance Data Scientist working on Natural Language Processing (NLP) and building end-to-end NLP applications.

I have over 7 years of experience in the industry, including as a Lead Data Scientist at Oracle, where I worked on NLP and MLOps.

I Share Practical hands-on tutorials on NLP and Bite-sized information and knowledge related to Artificial Intelligence.

#gpt3 #openai #nlp #sentencetransformers #embedding #artificalintelligence #machinelearning

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[arjunob]

You have explained everything very well and very patiently. 👍Thanks for these amazing tutorials Pradip!

[sathyag]

Hi Pradip, This is very very useful video for me because this is what I am searching to my real time project

[mansibisht]

Great work! Very useful video Pradip. Helped me a lot while doing POC at work. :)

[dhirajkumarsahu]

Hi Pradip, thank you for the video. It would be great if you could also talk about the challenges which face during the real time implementation.

[HazemAzim]

Thanks Pradip . super simple and informative 👌

[younginnovatorscenterofint]

This video was excellent. I'm going to have an interview on NlP OpenAI ChatGPT. What should I prepare for? Your suggestions will be helpful.

[youwang]

really appreciate your work as always, just wonder which one is better open AI embedding API or Transformer considering they all have same models for same functionality

[venkatesanr]

Thanks for your videos. Whether NER can be used for search engines using the tags and information retrieval. Any example link will be helpful and we are trying to do semantic search/map ocr output text with the input query text and final output is image based on the similarity. How openai can be fine tuning for semantic search?.
I have done experiments on sentence transformer for semantic search whether openai models are heavy weighted.

[sarathipriya]

in the video which db are you using to store the embeddings [video:playtime( 18:17)] for semantic search.

[sarathipriya]

how to create df[babbage_search ] and df[babbage similarity] because in the example it already have a dataframe, if we have to create how shoud i give

[seventfour]

What method would correspond to these problems? Can I use GPT-3 for these tasks?

"Fire" + "Mountain" --> "Volcano"
"Fire" + "Metal" + "Building" --> "Forge"
"Volcano" --> "Fire", "Mountain", "Environment", "Lava", "heat", "danger"

Help would be greaty appreciated! Thank you for the content!, I liked! <3

[Subhajit_]

Sir, Your Transformers playlist link showing invalid.

[mesaygemeda]

Thank you for a wonderful explanation. I have two questions. 1. The embedding model works for English only in my view so how we can use it for other languages? for example if we want to do it for other languages what we can do? 2. if it is possible to train the model with our data. what kind of data is needed? finally how can measure the accuracy of the similarity, semantic search, and classification? Thank you.

[otonomimusic]

I'm very unclear on classifications still - what is being classified to what? It looks like we're just comparing numbers with other numbers? what are the classifications?

[stanTrX]

Thanks. Is it still valid today? Any other easier better methods? I want to calculate similarities between two big lists for each item

[duetplay]

Quick question: what if the documents are 5000 words long, how can we apply this approach? or is there an alternative way to do it? Thanks in advance!

[sampriti]

Hey Pradip, I am building a discord bot that connects people based on the thoughts they send to the bot and messages on the server. Since im mew to the space wanted to get in touch with you to know more on how to get building this. Followed you on twitter, can you open your dms?

For starter, you mentioned gpt to be more accurate than models by huggingface? So should i follow this tutorial in building the bot thaay reads the messages, analyse thhe sentiments, topics of the message and then group them together?

[joao-pedro-alves]

I think this video would be much better if instead of using Python you'd showed the same example using curl. This way it would be much better to people adapt the example using any tech stack... There are a lot of things going on that only make sense for those who know Python and a lot of "magic" behind the libs...

[TauvicRitter]

Hmm, the difference in score is not what I call spectacular. Where do you set the threshold? Cannot simply say if similarity is above 80% then its the same if its less than 50% than its definitly not ok.