I
I made a version control for embeddings
I made a version control for embeddings
With the emergence of LLMs, there are numerous models that documents can be embedded in. EmbeddingBridge aims to ease the management of embeddings across models and having ownership. A convenient aspect is storing in the remote for larger embeddings. The project is still in its alpha stage and feedback/contributions are welcome.
Share cardActual performance
4points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
52%52% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
30%30% predicted probability of success on BetaList, based on ML models trained on real launch data.
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Incorrect prediction on native model
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