13ass13ass
13ass13ass t1_j9n98ui wrote
Reply to What. The. ***k. [less than 1B parameter model outperforms GPT 3.5 in science multiple choice questions] by Destiny_Knight
It’s fine tuned on the dataset. No big whoop
13ass13ass t1_iwo4lan wrote
Reply to comment by Singularian2501 in [R] Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning - Epochai Pablo Villalobos et al - Trend of ever-growing ML models might slow down if data efficiency is not drastically improved! by Singularian2501
Efficient zero is for RL with atari games though. How does it apply to things like large language models?
13ass13ass t1_ita7so1 wrote
Reply to comment by SFTExP in Thoughts on Job Loss Due to Automation by Redvolition
That’s what OP said tho…
13ass13ass t1_ir2qa5y wrote
As a hobbyist, I love it! This looks simple enough that I could implement it myself.
Except maybe I’d try changing out the google api with a database connection and have it perform sql queries as intermediate steps.
Could be fun! Eg put my family tree in the database and ask it “was my great uncle alive at the same time as my third cousin twice removed?” Etc.
13ass13ass t1_je5nc8b wrote
Reply to [D] The best way to train an LLM on company data by jaxolingo
You could look at the natural language -> sql query tools that are all the rage right now. I’d recommend checking out langchains sqlchainagent since it’s open source.