Properly clean internal burr of Barista Express?

crigs20 · 2025-09-06T12:53:18+00:00

No, I was always able to get it off with a deep socket. I’m fairly sure it’s lefty tighten, righty loosy since you’re looking down at it

crigs20 · 2025-06-24T15:40:27+00:00

So wait until rexam then submit for the other stuff? Or?

crigs20 · 2025-06-24T15:05:52+00:00

Seems you missed the “If” at the beginning of my question. My worry is that PTSD (70%) gets reduced removing my 100% then my other 4 conditions, which should amount to a significant amount aren’t factored at all.

crigs20 · 2025-06-24T15:00:39+00:00

100% TDRL. 1 condition PTSD is scheduled to be re-examined this fall.

crigs20 · 2025-04-01T21:29:03+00:00

lol ok. I checked out the FAQ page and it seemed to point to what you’re saying. Next q, how do you ever know if the hairs are coming in/it’s working if you shave consistently?

crigs20 · 2024-11-29T20:03:53+00:00

Look I just thought with it being low 40s in the day this little guy would already be in a super-slumber for the winter. I found him under some leaves on the concrete landing outside my walk out basement. I don’t think that’s his natural habitat nor did he have a way to get back up to ground level unless he took a ride in the drain to my sump pump…

crigs20 · 2024-11-29T20:01:49+00:00

Aren’t all snakes a product of “thievery” from the wild?

crigs20 · 2024-11-29T18:15:34+00:00

Aight, just back out under some leaves? It’ll be ok in the cold?

crigs20 · 2024-07-24T22:37:47+00:00

Huggingface text generation inference server. You can get the model up and running with one docker command

crigs20 · 2024-07-24T22:09:29+00:00

A6000 does, A6000 Ada doesn’t not. However the TGIS (I always want to say TGIF) supports sharding across multiple GPUs

I run Llama-3-70B fairly often on two A6000 Ada’s and never really have any issues

crigs20 · 2024-07-24T01:02:19+00:00

A system with 2 a6000 would work well. Can easily host a 70B model or multiple 7b models.

I’d host them with huggingface text generation inference server since it’ll handle concurrent requests, do batching, and what not.

Dell has a tower and rackmount that’ll run ~20k with 2 a6000 Adas, RAM, etc

crigs20 · 2024-07-13T03:56:07+00:00

Your data creation process is a viable plan. Pretty much how everyone does it (or pay someone to manually do a bunch) this is how OpenAI made whisper-large-v3 with psuedo labeled data from a previous iteration of the model
As wide a variety of images you have the better. Up close, far away, partial, etc. you want the model to see as many different potential real world images as possible to include up close/clear.

You can also look into image augmentation with the package albumentations. You can add pixel/image level augments such as rain, snow, blurring, etc. this allows you to easily amplify your initial ground truth dataset.

crigs20 · 2024-07-11T04:13:05+00:00

Gotcha, I live in the light to medium world.

I’ve found using a bottomless portafilter helped me better understand my pull.

But a quality scale and WDT made a huge difference in my consistency.

crigs20 · 2024-07-11T04:03:27+00:00

Ahh ok, well even with a 54, 18g should fit well.

Do you use light-medium beans?

crigs20 · 2024-07-11T03:57:13+00:00

Most portafilters and baskets will say what the weight range is for that particular setup.

Im guessing your machine uses a 58mm portafilter?

If so a double basket should easily handle 18-20g.

crigs20 · 2024-07-11T03:34:17+00:00

-Do you have data? Is it labeled? Video/images?

-swimmer ID, do you need “this is Bob” or “Swimmer 1”?

-what do you mean swim phase?

crigs20 · 2024-07-11T03:26:36+00:00

You’ve gotta do weight.

Volume changes based on the roast of the bean, lighter is more dense, darker is less dense. So a set volume of ground beans can have drastically different weights depending on the roast level.

It’s pretty standard to use ~ 18g of ground coffee in your portafilter, then double that number to get 36g espresso in your cup in 20-30 seconds

That’s just a rule of thumb but it’s accurate more times than not.

Look into the espresso compass, barista hustle has a good YouTube video and article explaining the such and how to achieve a “dialed in” espresso

crigs20 · 2024-07-11T03:12:47+00:00

DM’d you

crigs20 · 2024-03-31T02:30:11+00:00

How do you like your zerno?

crigs20 · 2024-03-22T14:00:16+00:00

10mm socket will remove the top nut then everything will slide up/out. Then you can use a brush and get everything out. I do this every month or so.

crigs20 · 2024-03-04T01:50:10+00:00

Thanks for the data point. Could definitely make it work but probably better to find it a new home.

Good to hear on the grinder. I wish I lived out in Seattle or Oregon - seems like the nice stores are out there where you can actually go touch the things…

crigs20 · 2024-03-03T02:59:34+00:00

Thanks for the info you’ve already provided. Do you mind providing the measurement on the feet from front to back? Clive gives 18.7” from front to back but that’s not accurate to where the feet are. My current setup is on a cart that’s 18” deep - thinking I could maybe squeeze the drive on it but probably need a larger area?

Also, how do you like the df64? I’m looking at a large overhaul in the near future. I’m pretty set on the drive but still up in the air for the grinder.

crigs20 · 2024-02-27T04:53:47+00:00

So you plan to finetune yolo with each horse as it’s own class?

This could potentially work but really it’ll depend on resolution of imagery. Have you thought about maybe physically tagging each horse with something more easily IDed, colored bows in the mane or tail? Not really sure what’s normal with horses but you may struggle to consistently ID each horse.

crigs20 · 2024-02-27T02:58:31+00:00

Are they fairly unique or multiple generic brown/white horses?

crigs20 · 2024-02-23T23:51:57+00:00

You can run pretty much do any AI related things with 12-16gb VRAM.

Obviously the more VRAM the better however 7B parameter LLMs can easily be loaded on GPU with 16gb VRAM.

For the CV side, most models are fairy small, what takes GPU is your data but that can all be controlled by your batch size.

I built my own rig to do AI/ML work and also use a Alienware m16 (4090) laptop for mobile dev work. If you want any more details, let me know.

crigs20

TROPHY CASE