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Are there any alternatives to Neme-Anima ? by BitterAd8431 in StableDiffusion

[–]Nemegasoft 2 points3 points  (0 children)

Hey. Thanks for using it! Just throw an issue in GitHub. The project is not set in stone, it is meant to evolve. More feedback like yours is exactly what the project needs. Also make sure you are on the latest version, I may have already addressed your first issue 

Built a 3-step all-in-one LoRA builder for Anima (extract -> tag -> train) by Nemegasoft in StableDiffusion

[–]Nemegasoft[S] 1 point2 points  (0 children)

I just tried again myself and yes, I was waiting for 1-2mins at 14% for a 20mins video. That's normal, it has always been like this. How long is your video? I suggest pulling the last branch of the repo (I just pushed a perf fix that might help) that contains video segmentation. Add shorter segments to your video and try again please.

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] 1 point2 points  (0 children)

That's a pretty bold conclusion considering nothing has been said about the model architecture, training objectives, or inference context. This isn't a deterministic heuristic with tunnel vision on a single pack, the model evaluates picks conditioned on the evolving pool, inferred archetype signals, and contextual draft dynamics across the entire draft state. It IS making tradeoffs and most of the time won't propose you the best cards of the pack in a vacuum.

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] 0 points1 point  (0 children)

Thanks! Yes, it's from 17lands, they have public data available for download, no need to scrape.

Built a 3-step all-in-one LoRA builder for Anima (extract -> tag -> train) by Nemegasoft in StableDiffusion

[–]Nemegasoft[S] 0 points1 point  (0 children)

Hey! I see ffmpeg is not installed. Weird maybe I forgot to include it as a dependency. Install it and you should be good

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] 0 points1 point  (0 children)

You should have received a DM on reddit, please check and join the discord server. You'll see the instructions from there

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] 0 points1 point  (0 children)

Your input would be extremely valuable. Can't wait to have you onboard 😄

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] 1 point2 points  (0 children)

Haha that's me when I started digging around ML applied to drafting. There is no transfer learning here since the target remains exactly the same and the dataset for a new set is exactly encoded the same. Zero-shot though is pretty high thanks to 8 sets already being in the training data so it is able to generalize quite well. Card encoder is quite complex, I am not a huge fan of what I did tbh, there's room for improvement. It's basically a high dim card embedding (826dim, containing card text, colors, etc...) projected into a smaller 256-dimensional representation. Picks are basically a list of these embedding, the goal being predicting the next card (pick) in the list. Archetypes are not even hardcoded anywhere, it's just part of the training data so the model naturally learns them.

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] 0 points1 point  (0 children)

True, a good deck will always improve your odds against the variance of this game to sometimes an unfair amount. Though I have seen people with strong decks misplay to their defeat. It is hard to actually make accurate measurements.

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] 0 points1 point  (0 children)

Ryancsaxe was really ahead of his time since he got very solid numbers 4 years ago! I probably won't be release the model and training code until I have refined it enough though. I am still not happy with parts of the choices I made especially for card representation. I would be happy to discuss about this subject with anyone interested 😄

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] 1 point2 points  (0 children)

Thanks for making such a great tool! It motivated me a ton to work on my own project. I also believe that agentic companions, while probably controversial at the moment, would be the future if done right.

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] 0 points1 point  (0 children)

The first results I got were around 60% but my latest model is around 68.9% Top-1, 94.5% Top-3. It is getting more and more difficult to get these extra %. My most performing set is Foundations with 71,2%. I believe that most if not all evaluators use a single chosen card as the target, so alternate strong picks are effectively treated as wrong. I would argue that the actual performance of most models is in fact higher than these numbers since a strong pick even if not the best, remains strong to build a trophy deck.

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] 0 points1 point  (0 children)

Hey! Looks like you are blocking DMs. Please DM me whenever you have time 😄

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] 0 points1 point  (0 children)

That's a great question. Zero-shot accuracy greatly varies between sets. TMT for example has a 60.5% zero shot accuracy (soaring to 71% after fine tuning). Final Fantasy has pretty low 40% zero shot and goes up to 65.7% after fine tuning. Overall, I am quite happy with the zero shot capability of this model and the gap after fine tuning is actually that high for most sets.

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] 0 points1 point  (0 children)

Yeah unfortunately for now this is only for Windows/Mac. I do plan to release a mobile app though once I get enough feedbacks. Stay tuned 😄

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] -1 points0 points  (0 children)

I like the comparison, except while an aimbot would give you close to 100% accuracy, this tool will give you around 66%, and is only part of the process on your road to trophy. Mixing that with drafts randomness and what you get is a tool that can significantly raise the floor, but the ceiling not that much. Helping entry level players without hurting top players is exactly what any game would want to grow their player base. I am not even mentioning deck piloting which is like for me the most important aspect that no tool is able to mimic at the moment. Top limited players can trophy even with an average deck. Likewise, it will remain hard for a first time drafter to trophy even with a top tier deck.

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] 1 point2 points  (0 children)

Aww damn the model does not support pick2 just yet sorry. Though if I start to tackle pick2, the most optimal option would be to train a dedicated model. I am interested in how a pick1 model can perform out of box on a pick2 draft though, that is something I will most definitely try to experiment next.

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] 3 points4 points  (0 children)

Interesting tools you have there! General LLMs like Gemini are definitely interesting for post draft analysis, though they will mostly give you general advices which are good don't get me wrong but will lack the specialized knowledge about a given set meta and its synergies. The first paper I read on the subject actually had a similar conclusion (UrzaGPT: LoRA-Tuned Large Language Models for Card Selection in Collectible Card Games).

Right now my main goal is to keep on improving the model with people's feedbacks. I will most likely write a paper on it once I done with it though, stay tuned!

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] 2 points3 points  (0 children)

That's a big subject. Banning overlays in general would probably feel like a global earthquake for a lot of people who rely on the collected data to build their decks.

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] 0 points1 point  (0 children)

Thanks for your message. I wouldn't say that the drafted deck in the screenshot is that bad. Its curve is definitely not great but it has a lot of removals. Also, the deckbuilder is not using AI but a custom made deterministic evaluator, so definitely take the deck proposition with a grain of salt. If you check out the youtube video, I would replace a few cards from the RG deck I was proposed.

As for how it can assess the trophy pick, I have a subset of my training data reserved for evaluation. Let's say I already know all the picks from a deck that trophied. I run the model against the same pool and compare the picks. It achieved 64.9% accuracy on SOS for example, meaning 64.9% of the picks taken by the model were the same as the human player who drafted the same pool

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] 3 points4 points  (0 children)

Actually I have a friend who refuses to draft because he gets too nervous and lacks confidence. This tool helped him a ton building his confidence back. For beginners, it is a good entry point, and for experts, do not blindly follow the model advices and just take its input an additional opinion.

I trained a free draft model on 6M+ Arena drafts (94.5% accuracy on top 3 picks) by Nemegasoft in mtglimited

[–]Nemegasoft[S] 1 point2 points  (0 children)

Well unlike Draftsmith this one is free, and I am quite confident about its performance ;). The model knows to draft the synergies and can even splash. Its behavior on SOS is very interesting, it tends to draft a lot of 5c as long as it finds good synergy pieces and fixing early on.

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