101–110 of 160 posts
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1.5B models can run on CPU inference at around 12 tokens per second if I remember correctly.
Ingesting multiple code files will take forever in prompt processing without a GPU though, tg will be the least of your worries. Especially when you don't append but change it in random places so caching doesn't work.
Sometimes when I use a plugin like this I get reminded just how much of a productivity nerf it is to code without an autocomplete AI. Honestly in my opinion if you write a lot of boilerplate code this is almost more useful than something like Claude Code, because it turbocharges your own train of thought rather than making you review someone else's, which may not align with your vision. This is a really good plugin.…
Hopefully not too offtopic: why so much boilerplate? I see most would-be-boilerplate code refactored so the redundant bit becomes a small utility or library. But most of what I write is for research/analysis pipelines, so I'm likely missing an important insight. Like more verbose configuration over terse convention? For code structure, snippets tempting[1] ("iff[tab]" => "if(...){...}") handles the bare conditional/l…
You bring up a good point with snippets though, and I wonder if that would be good information to feed into the LLM for autocomplete. That snippet is helpful if you want to write on condition at a time, but say you have a dozen conditions if statements to write with that snippet. After writing one, the LLM could generate a suggestion for the other 11 conditions using that same snippet, while also taking into consideration the different types of values and what you might be checking against.
As for RAM/processing, you're not wrong there, but with specialized models, specialized hardware, and improvements in model design, the number of people working under such restricted environments where they are concerned about resource use will decrease over time, and the utility of these tools will increase. Sure a lower-tech solution works just fine, and it'll continue to work fine, but at some point the higher-tech solution will have similar levels of friction and resource use for much better utility.
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I'd stay away from ollana, just use llama.cpp; it is more up date, better performing and more flexible.
But you can't just switch between installed models like in ollama, can you?
Sometimes when I use a plugin like this I get reminded just how much of a productivity nerf it is to code without an autocomplete AI. Honestly in my opinion if you write a lot of boilerplate code this is almost more useful than something like Claude Code, because it turbocharges your own train of thought rather than making you review someone else's, which may not align with your vision. This is a really good plugin.…
Hi, I tried the model and I am super impressed by the performance/quality. Thanks for making this open source! I am the author of this Neovim plugin for edit completions. I was able to integrate it with the Sweep Edit model. For anyone who is interested: https://github.com/leonardcser/cursortab.nvim
Hi, I tried the model and I am super impressed by the performance/quality. Thanks for making this open source! I am the author of this Neovim plugin for edit completions. I was able to integrate it with the Sweep Edit model. For anyone who is interested: https://github.com/leonardcser/cursortab.nvim
Is there a port of this to Emacs or integration with gptel?
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Better than the one that ships with Jetbrains? I did buy their $100/yr AI but its about to run out.
Definitely better. Next edit makes a difference. But it is not free, I think I pay $10/month.
Hi, I tried the model and I am super impressed by the performance/quality. Thanks for making this open source! I am the author of this Neovim plugin for edit completions. I was able to integrate it with the Sweep Edit model. For anyone who is interested: https://github.com/leonardcser/cursortab.nvim
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I've been using it with the Zed editor and it works quite well! Congrats. This kind of AI are the ones I like and I'm looking to run in my workstation.
Could you give the gist / config on how you made it work with Zed ?
{
"agent": {
"inline_assistant_model": {
"model": "hf.co/sweepai/sweep-next-edit-1.5B:latest",
"provider": "ollama",
},
}
}