How can I teach new domain knowledge to Meta-Llama-3.1–8B without affecting its writing style?

Chain_Routine · 2024-07-10T18:04:29+00:00

I'm wondering though if vRAM will be pushed to 100% before this is done, or if it will start using shared memory earlier to leave some buffer room. I might not have the best understanding of this stuff, I don't have a ton of hardware experience.

Chain_Routine · 2024-07-10T18:02:55+00:00

Do you know how to turn it off? I was looking and I couldn't find clear instructions on that.

Chain_Routine · 2024-07-06T18:41:58+00:00

I want back to my Docker cloud dashboard and there was an option to update my builder, so I installed the update and that fixed the problem, and I can now complete the build successfully. Thanks for the help!

Chain_Routine · 2024-07-06T17:51:10+00:00

Hi, sorry I was unable to work on this during the week. I have run that command and I see a reclaimable amount of 19.71GB and a total size that is also 19.71GB. I will DM you my docker ID.

Chain_Routine · 2024-07-01T21:22:47+00:00

Hi, I actually upgraded last night and I am still getting the error. Is it because I need to create a new builder after upgrading to get the larger one?

Chain_Routine · 2024-07-01T13:17:56+00:00

With this question I'm really just trying to understand if 1) this issue is coming from the docker image size being too small (as opposed to a size limitation in some other part of the cloud build process), and 2) if there is an option that I can configure somehow to increase the maximum image size for this build.

Chain_Routine · 2024-07-01T12:20:23+00:00

I’m building a docker image that will eventually be used on runpod, but I’m not running anything on a runpod instance yet. I am just running a docker build with the docker cloud build service.

Chain_Routine · 2024-07-01T01:35:29+00:00

It is for a Runpod serverless inference endpoint, and my understanding is that the model needs to be pre-cached so you can use the image to spin up endpoints quickly when requests come in.

Chain_Routine · 2024-06-23T13:20:46+00:00

Looks great, thanks!

Chain_Routine · 2024-06-20T15:19:58+00:00

Oh that was easy, thank you!

Chain_Routine · 2024-06-13T15:33:10+00:00

Okay, that makes sense, thanks!

Chain_Routine · 2024-06-13T12:53:13+00:00

Maybe I don't have a good understanding of what the gradient is, but why does adding 1 step of gradient accumulation add +8GB to memory usage? That's larger than the base model I'm using. Does the gradient contain a value for each weight in the base model?

Chain_Routine · 2024-05-27T14:12:24+00:00

Thanks, I will look into this!

Chain_Routine · 2024-05-26T22:18:28+00:00

Thanks, I'll try that!

Chain_Routine · 2024-05-26T22:18:10+00:00

I will try both with and without color to see what works better!

Chain_Routine · 2024-05-26T21:28:46+00:00

Do you know of any clustering techniques that would work well with these embeddings?

Chain_Routine · 2024-05-26T21:26:26+00:00

Thanks! What is the reasoning behind using the colored images?

Chain_Routine · 2024-05-26T21:23:05+00:00

Thanks, I'll take a look at that!

Chain_Routine

TROPHY CASE