eborgnia

4 ms·

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by eborgnia 11mo ago
How do you expect it to be priced? We do give discounts for high volume users.
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by eborgnia 11mo ago
Hey, happy to answer! The manual evals we did showed that both morph-v3-fast and morph-v3-large had significantly more smoothing and hallucination behaviors. It's hard to know for sure because their methods aren't public, but my g
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A Year of Fast Apply – Our Path to 10k Tokens per Second(relace.ai)
48 points by eborgnia 11mo ago|6 comments
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by eborgnia 1y ago
Glad it's working out -- thanks for the support :)
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by eborgnia 1y ago
The diffusion approach is really interesting -- it's something we haven't checked out for applying edits just yet. It could work quite well though! You can definitely use it for markdown, but we haven't seen anyone test it fo
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by eborgnia 1y ago
Haha, we think of "vibe-coded codebases" as codebases produced by nontechnical users that are using an AI tool
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by eborgnia 1y ago
Adding extra structural information about the codebase is an avenue we're actively exploring. Agentic exploration is a structure-aware system where you're using a frontier model (Claude 4 Sonnet or equivalent) that gives you an im
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by eborgnia 1y ago
Happy to collaborate, shoot us an email at info@relace.ai :)
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by eborgnia 1y ago
Hey, these are really interesting points. The question of agentic discovery vs. one-shot retrieval is really dependent on the type of product. For Cline or Claude Code where there's a dev in the loop, it makes sense to spend more money
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by eborgnia 1y ago
Cline orchestrates all the models under the hood, you could use our apply model with Cline. Not sure what model they are using for that feature right now
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by eborgnia 1y ago
We trained it on over a dozen languages, with a bias towards Typescript and Python. We've seen it work on Markdown pretty well, but you could try it on plaintext too -- curious to hear how that goes
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by eborgnia 1y ago
Open source git repos are a really good place to get data -- it requires a lot of munging to get it into a useful format, but that's the name of the game with model training. It's on the roadmap to make public evals people can use
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by eborgnia 1y ago
Hey, really appreciate the detailed sign up journey here! Getting the simplest flow is hard, and it's something we obsess over. The docs have been a work in progress for the past couple of months, but now that they are getting better I
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by eborgnia 1y ago
We have a few benchmarks on docs.relace.ai in the model overview sections. Any ideas on other benchmarks you'd like to see are welcome though
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by eborgnia 1y ago
Thanks for the support!
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by eborgnia 1y ago
Thank you :) Please do reach out, we love talking to builders in this space & would love to share notes & give you free access. eborgnia@relace.ai
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by eborgnia 1y ago
Hey -- good question! We're focused on a narrower task right now that aims to save frontier tokens (both input & output). Our merge + retrieval models are simply smaller LLMs that save you from passing in too much context to Sonnet
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Launch HN: Relace (YC W23) – Models for fast and reliable codegen
111 points by eborgnia 1y ago|51 comments