brrrrrm

11 ms·

91.
by brrrrrm 2y ago
First I would calculate the number of tokens you actually need. If its less than 32k there are plenty of ways to pull this off without RAG. If more (millions), you should understand RAG is an approximation technique and results may not be
92.
by brrrrrm 2y ago
Why not just self sign a local cert? Its really easy to do (ask an AI for a relevant example in your language of choice)
93.
by brrrrrm 2y ago
Guh, wish i could delete this now that the title was updated. the original title (shown on the linked page) wasn't super clear
94.
by brrrrrm 2y ago
Yep the title was updated.
95.
by brrrrrm 2y ago
Kernel is an overloaded term for GPUs. This is about the linux kernel
96.
by brrrrrm 2y ago
Apple watch has this feature
97.
by brrrrrm 2y ago
I meant 8b -> 8billion rather than 70b
98.
by brrrrrm 2y ago
Mine is also an m1. Just use llama3, its 8b quantized by default
99.
by brrrrrm 2y ago
I use my mac mini exactly as described by the parent post but using ollama as the server. Super easy setup and obv chatgpt can guide you through it
100.
by brrrrrm 2y ago
Best chatgpt could do was deltas by lines https://github.com/bwasti/bram.town/blob/main/server.ts#L142 Perfect is the enemy of dinner
101.
by brrrrrm 2y ago
Since macOS High sierra apparently, 2017 release :(
102.
Show HN: Collaborative ASCII Drawing with Telnet(jott.live)
101 points by brrrrrm 2y ago|18 comments
103.
Show HN: Eye-Tracking for Immersive 3D(jott.live)
1 points by brrrrrm 2y ago|1 comments
104.
by brrrrrm 2y ago
restricts freedom in one of the parameters (A) to make training substantially more efficient (easier for a GPU to churn through). the actual flops involved are similar to the original SSM-based version, but that's harder to formulate a
105.
by brrrrrm 2y ago
I’ve definitely met people whose stats are juiced. Probably not as good at scrolling tiktok as me tho
106.
by brrrrrm 2y ago
This and the lack of infix operators was one of the main reasons Shumai stalled out. The language has so much to offer, but JS just isn't quite there for native ML coding
107.
Show HN: Locally run a "blue text" bot (llama3)(github.com)
4 points by brrrrrm 2y ago|1 comments
108.
by brrrrrm 2y ago
I think it's a trap of visual elegance. When you start thinking of models this way you miss the way a lot of models are actually written. E.g. how do you represent an online fine-tuning process? I want to randomly switch between a re
109.
by brrrrrm 2y ago
I think it uses TF's graph construct which has that built in? it's like a weird mix of dataflow and control flow graphs.
110.
by brrrrrm 2y ago
I wonder if you could track provenance by operating at the highest layer of the dispatcher and capture any calls to GPU operations (ala Cuda Graph)? > in the unused bits I feel like this is a PT rite of passage :P
111.
by brrrrrm 2y ago
I've never really understood the point of these visualizer things. The idea that a model is always well represented by a directed acyclic graph seems extremely dated. I really would love a PyTorch/JAX profiler that shows, in anno
112.
by brrrrrm 2y ago
A single 8xH100 node hits 15.6 fp16 petaFlops
113.
by brrrrrm 2y ago
Eye of the beholder I guess. I personally wouldn’t offer moral judgement on the uninvented
114.
by brrrrrm 2y ago
Have you been on r/localllama? I’d wager this tech will make it to open source and get tuned by modern creatives just like all the text based models. Individuals are a lot more empowered to develop in this space than is commonly echoe
115.
by brrrrrm 2y ago
I use it all the time?
116.
by brrrrrm 2y ago
if anything the controversy increased sales. I watched the ad and thought it was pretty cool
117.
PyTorch is live streaming their meeting on twitch(twitch.tv)
2 points by brrrrrm 2y ago|0 comments
118.
by brrrrrm 2y ago
It mentions immersion methods and then never revisits it :( I used to use a Chemex but found the whole process so fickle and involved. I've since switched to a Clever dripper (similar to the hario switch) and found that my coffee life
119.
by brrrrrm 2y ago
“Increasing control points” hides a lot under the covers here. Your answer and the paper provide virtually no reason to believe one type of continuous function approximation is better than another. The comparisons made are superficial and
120.
by brrrrrm 2y ago
doesn't KA representation require continuous univariate functions? do B-splines actually cover the space of all continuous functions? wouldn't... MLPs be better for the learnable activation functions?

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