u/Timotheeee1

36.2k post karma · 5,560 comment karma · joined Sep 2014

  1. 22points

    My IRL experience with every personality type (self.INTP) [Sarcasm... Or is it?]

    21 comments

  2. 38points

    Who needs artillery (i.redd.it)

    7 comments · source

  3. 16points

    Hard Mode Marcus & Faleris beaten in 10 seconds (Credit: The Pal Professor) (v.redd.it) [Video]

    1 comments · source

  4. 111points

    New sampling method that boosts reasoning performance and can be applied to any existing model (arxiv.org) [News]

    3 comments · source

  5. 26points

    Base building be like (i.redd.it) [Meme]

    4 comments · source

  6. 247points

    GPT-4.5 cost (i.redd.it) [New Model]

    118 comments · source

Timotheeee1

in about half of these cases the person actually did the test and told me, but fair enough I might be wrong about some of the rest

Timotheeee1

from a large stockpile built up over ages

Timotheeee1

it's just the kerafactor cap but cheaper

Timotheeee1

this is an LED cap, which is useless

Timotheeee1
Timotheeee1

usually yes, because the web versions tend to include enormous system prompts with hundreds of instructions, while the API has none

Timotheeee1

Anthropic shows the first 1k tokens or so, then a summary

Timotheeee1

go to meetup events

Timotheeee1

what happens if you instead use a specialized calibration dataset that contains only code or only english writing? you could probably prune the 235B down quite a lot more and make several specialist models.

Timotheeee1

what will the speed and cost be with a reasonable batch size once available on openrouter?

Timotheeee1

only the boss drops the schematic

Timotheeee1

actually I did build beds after building all of the farms

Timotheeee1

closed-source frontier models can be used to generate high quality data for fine-tuning local models that are specialized in specific tasks. (especially this one as it shows the reasoning traces)

they also provide a preview of the capabilities that open models will likely have in the future.

Timotheeee1

try asking in the unsloth discord

Timotheeee1

no, gradient checkpointing only offloads activations, but my idea would be to additionally offload model weights too

Timotheeee1

It would be cool if when doing QLoRA you could offload some layers of the model to the CPU and have them streamed to the GPU over PCIe as they are needed. in theory this shouldn't make the speed that much worse since PCIe has 63GB/s, enough bandwidth to stream the weights of a 32B 4 times per second, and it usually takes much longer than that do process one batch. this could allow for fine-tuning of larger models on colab and local hardware

Timotheeee1

It was solved a few months ago: https://arxiv.org/pdf/2409.12517v1

Timotheeee1

did you ever manage to fix this?

Timotheeee1

I think your project could still be useful for applying changes in a big file with 20k tokens, as you can't really expect the model to just re-output everything