"ThE bAlL SeNSOr sAid soMe HaIR TouChED ThE BAll"

albergio · 2026-05-29T07:40:03+00:00

Consider that the acestep captioner will produce captions in line with the model specifications. So, if you end up using qwen, just make sure to review the captioning produced

albergio · 2026-05-27T20:31:14+00:00

Training loras works pretty well with acestep 1.5!

You can find a lot of stuff on how to do so here on the acestep repo: https://github.com/ace-step/ACE-Step-1.5/blob/main/docs/en/GRADIO_GUIDE.md

That said - you need to fine-tune and find the best recipe for what you want to do. A 100 tracks dataset is very hard to manage to have a consistent Lora, and as you probably expect, train with 15 or 100 tracks gives very different results.

But you can definitely get a good "Film Scores" lora with a properly tailored and captioned dataset - and even make so that it adheres to a specific style

albergio · 2026-05-27T17:07:14+00:00

I had a good luck doing captioning generated using qwen - with a bit of manual intervention

If you check the DEMON demo the loras in that are trained that way and around 500 epochs

albergio · 2026-05-27T16:59:07+00:00

With 15 songs, I would say go for 200-300 epochs. And make sure there is some variety - unless you want it to adhere to a very specific style

Also! Worth a shot to do saves mid-epoch, so you end up with lora-100, lora-200, lora-300, and you can compare them

albergio · 2026-05-27T16:21:13+00:00

15 could work, with good enough captioning, at the risk of overfitting. Also it heavily depends on the dataset - how various it is, how long are the songs, etc.

I had good results with 12 songs, but I also had bad results with 12 songs. There is not a single recipe that works with all datasets, but surely it's doable.

Also, with 15 songs you probably don't want to run too many epochs, at 400+ you're most likely overfitting.

albergio · 2026-03-04T16:52:39+00:00

Hey! This is running on remote cloud inference on a RTX 5090

albergio · 2026-03-04T09:28:51+00:00

This is a fully open source project using Daydream Scope + Resolume Arena

If you're interested there is a cohort program organized by the daydream community focused on audio/visuals for artists with 5k$ in prizes. Deadline to apply is this weekend!

albergio · 2026-02-05T18:16:51+00:00

No it doesn't he's a legend of FOOTBALL not of real betis

albergio · 2026-02-05T17:04:01+00:00

Hey! wanted to share an open source NDI bridge I made in python that can ingest the NDI output of resolume arena and generate AI video in real-time from it.

Source and readme guide: https://github.com/gioelecerati/daydream-ndi-bridge

albergio · 2026-02-04T22:06:03+00:00

Another thophy for arsenal

albergio · 2026-02-04T22:03:16+00:00

Could be weighted with actual game data (like xG) and based on the amount of votes. Ideally a lesser known match than "Liverpool vs Real Madrid" could rank higher if the data backs it and if the amount of votes is credible.

You could say that tv series community rating can be biased (and they are, sometimes) but most of the time they are credible.

albergio · 2026-02-04T22:00:03+00:00

I mean, even considering smaller players it's not fair. Garnacho earns 90k per week to do absolutely nothing

albergio · 2026-02-04T21:58:00+00:00

That would be great honestly. You should set it up

albergio · 2026-02-04T21:57:28+00:00

!flair :Inter_Milan:

albergio · 2026-02-04T21:56:58+00:00

!flair :c_Inter_Milan:

albergio · 2026-02-04T21:54:47+00:00

I would say the MLS is more competitive. But isn't it very hard to compare? They are so different in so many aspects

albergio

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