Dumbar
A smrt, no, smart, ok, no dumb smartbar for Ollama (by JerrySievert)
triton
Development repository for the Triton language and compiler (by triton-lang)
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Dumbar | triton | |
---|---|---|
2 | 30 | |
51 | 11,277 | |
- | 6.2% | |
4.6 | 9.9 | |
9 months ago | 4 days ago | |
JavaScript | C++ | |
MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Dumbar
Posts with mentions or reviews of Dumbar.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-09-26.
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Show HN: Ollama for Linux – Run LLMs on Linux with GPU Acceleration
give Dumbar a try, since you're on macOS! https://github.com/JerrySievert/Dumbar
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Dumbar, a Not So Smart Menubar App
I created this to fill a need, accessing those silly LLMs from the menu bar instead of a web browser or command line.
It relies 100% on Ollama, but gives you an easy way to make queries against multiple models, and provides a few sample modelfiles for you.
open source, of course.
https://github.com/JerrySievert/Dumbar to skip the blog post and go straight to the code and release.
triton
Posts with mentions or reviews of triton.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-09-26.
- OpenAI Triton: language and compiler for highly efficient Deep-Learning
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Show HN: Ollama for Linux – Run LLMs on Linux with GPU Acceleration
There's a ton of cool opportunity in the runtime layer. I've been keeping my eye on the compiler-based approaches. From what I've gathered many of the larger "production" inference tools use compilers:
- https://github.com/openai/triton
- Core Functionality for AMD #1983
- Project name easily confused with Nvidia triton
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Nvidia's CUDA Monopoly
Does anyone have more inside knowledge from OpenAI or AMD on AMDGPU support for Triton?
I see this:
https://github.com/openai/triton/issues/1073
But it's not clear to me if we will see AMD GPUs as first class citizens for pytorch in the future?
- @soumithchintala (Cofounded and lead @PyTorch at Meta) on Twitter: I'm fairly puzzled by $NVDA skyrocketing... (cont.)
-
The tiny corp raised $5.1M
I thought this was a good overview of the idea Triton can circumvent the CUDA moat: https://www.semianalysis.com/p/nvidiaopenaitritonpytorch
It also looks like they added MLIR backend to Triton though I wonder if Mojo has advantages since it was built on MLIR? https://github.com/openai/triton/pull/1004
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Anyone hosting a local LLM server
I'm pretty happy with the setup, because it allows me to keep all the AI stuff and its dozens of conda envs and repos etc. seperate from my normal setup and "portable". It may have some performance impact (although I don't personally notice any significant difference to running it "natively" on windows), and it may enable some extra functionality, such as access to OpenAi's Triton etc., but that's currently neither here nor there.
- Triton: Runtime for highly efficient custom Deep-Learning primitives
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Mojo – a new programming language for all AI developers
Very cool development. There is too much busy work going from development to test to production. This will help to unify everything. OpenAI Triton https://github.com/openai/triton/ is going for a similar goal. But this is a more fundamental approach.