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appvoid
appvoid
AI & ML interests
singularity through byte-level tokens and small language models
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repliedto their post about 3 hours ago
It's 2026 and there are no instantaneous/fast vision language models for cpus yet. That's another free idea. repliedto their post about 7 hours ago
It's 2026 and there are no instantaneous/fast vision language models for cpus yet. That's another free idea. repliedto their post about 8 hours ago
It's 2026 and there are no instantaneous/fast vision language models for cpus yet. That's another free idea.Organizations
replied to their post about 3 hours ago
replied to their post about 7 hours ago
a little bit skeptic about 1m parameters though
Plausible on server cpus, but maybe lower for normal cpus idk
Yeah on server cpus actually makes sense
replied to their post about 8 hours ago
a little bit skeptic about 1m parameters though
posted an update about 9 hours ago
Post
51
It's 2026 and there are no instantaneous/fast vision language models for cpus yet. That's another free idea.
- 6 replies
updated a
Space 2 days ago
posted an update 2 days ago
Post
106
CaraArchive highlights a broader reality of putting data online: once something is publicly accessible, it becomes extremely difficult to guarantee that it will remain under your control.
If there is information or artwork that you absolutely do not want copied, archived, scraped, downloaded, or used by others, the safest option is still not to publish it publicly in the first place. That may sound obvious, but the internet was fundamentally designed to move and reproduce information, and there are countless ways to retrieve publicly accessible images:from ordinary browser tools and web scraping to automated or agentic systems.
That does not mean artists should simply accept every possible use of their work. Artists deserve meaningful control, attribution, compensation, and reasonable ways to express how their work may be used. But treating the technology and peopple using it itself as the enemy is unlikely to solve the underlying problem.
There probably isn't a technical solution that can make a publicly visible image simultaneously viewable by everyone and impossible to copy. The realistic goal should therefore be to create better norms, incentives, licensing systems, and tools around how that content is used.
Like, we can imagine a future where every artist gets his/her own credentials and some kind of fingerprint done just like blockchain works. But that requires substantial cooperation among organizations, companies and individuals.
Technology and art are not inherently opposing sides though.
If there is information or artwork that you absolutely do not want copied, archived, scraped, downloaded, or used by others, the safest option is still not to publish it publicly in the first place. That may sound obvious, but the internet was fundamentally designed to move and reproduce information, and there are countless ways to retrieve publicly accessible images:from ordinary browser tools and web scraping to automated or agentic systems.
That does not mean artists should simply accept every possible use of their work. Artists deserve meaningful control, attribution, compensation, and reasonable ways to express how their work may be used. But treating the technology and peopple using it itself as the enemy is unlikely to solve the underlying problem.
There probably isn't a technical solution that can make a publicly visible image simultaneously viewable by everyone and impossible to copy. The realistic goal should therefore be to create better norms, incentives, licensing systems, and tools around how that content is used.
Like, we can imagine a future where every artist gets his/her own credentials and some kind of fingerprint done just like blockchain works. But that requires substantial cooperation among organizations, companies and individuals.
Technology and art are not inherently opposing sides though.
updated a
Space 2 days ago
published a
Space 2 days ago
reacted to mlabonne's post with โค๏ธ 6 days ago
Post
3458
Deploy local agents everywhere with LiquidAI/LFM2.5-2.6B
Unlike agents that depend on cloud APIs, local agents give you free inference, low latency, and real privacy.
Removing the per-token cost changes how developers build: agents can now be massively parallelized on local hardware, running background tasks that burn through millions of tokens at no marginal cost!
Unlike agents that depend on cloud APIs, local agents give you free inference, low latency, and real privacy.
Removing the per-token cost changes how developers build: agents can now be massively parallelized on local hardware, running background tasks that burn through millions of tokens at no marginal cost!
- 7 replies
liked a
model 6 days ago
replied to Banaxi-Tech's post 6 days ago
Good job
reacted to Banaxi-Tech's post with ๐ 6 days ago
Post
2901
We're excited to release BananaMind 2 Pro, our final version of the Pro model.
Trained on 100B tokens it performs extremely good for its token and size class.
The training took 22 days on one RTX 5070 Ti.
Check it out at
BananaMind/BananaMind-2-Pro
We did not release a Chat version yet because it regressed. Release Later.
Follow us to know when BananaMind 2 Ultra releases and support us at
BananaMind
@Banaxi-Tech
@vovaRL
@DedeProGames
Trained on 100B tokens it performs extremely good for its token and size class.
The training took 22 days on one RTX 5070 Ti.
Check it out at
BananaMind/BananaMind-2-Pro
We did not release a Chat version yet because it regressed. Release Later.
Follow us to know when BananaMind 2 Ultra releases and support us at
@Banaxi-Tech
@vovaRL
@DedeProGames
- 19 replies
liked a
model 7 days ago
replied to their post 7 days ago
Moreover, the implications are that finetuning models already pretrained on structure could outperform ones starting from scratch.
posted an update 8 days ago
Post
161
If you lack ideas for a cool model, here's one.
Train a model from scratch on wikipedia with one twist: the tokenizer changes the actual token ids used on every sample fed. If somehow still learns English, you have made an astonishing discovery.
You would have answered the question: Can a model learn human languages from structure alone?
Train a model from scratch on wikipedia with one twist: the tokenizer changes the actual token ids used on every sample fed. If somehow still learns English, you have made an astonishing discovery.
You would have answered the question: Can a model learn human languages from structure alone?
- 2 replies
replied to Banaxi-Tech's post 8 days ago
I'm pretty sure you need to check the memory window of that model before training. Check falcon-h1-tiny blogpost to understand what I mean.
reacted to Banaxi-Tech's post with ๐ฅ 8 days ago
Post
2741
Today we wanted to release BananaMind 2 Pico, our smallest model yet at ~0.9M parameters. Instead, we accidentally ran a very expensive experiment on what happens when you push a tiny model way past its useful token budget.
Short version: we trained on 200B tokens (~222K:1 tokens-per-parameter). The model peaked at 20B tokens with an INT Index of 4.55, then degraded monotonically over the next 160B to 3.31 โ a 27% regression. Three of four Open SLM benchmarks were worse at the end of training than they were at 10% through.
The useful compute-optimal range for Pico-tier models looks like ~22Kโ30K tokens per parameter. Ratios like 7K:1, 15K:1, and 22K:1 all work fine โ TinyStories and most sub-3M community models sit in this range. Push much further and benchmarks start rotting.
Follow us for more:
BananaMind
@vovaRL
@Banaxi-Tech
Full writeup with all checkpoints, the Chinchilla-ratio control run, and the schedule-vs-overtraining analysis: https://huggingface.co/blog/Banaxi-Tech/ovdadadadd
And if anyone, i dont know the reason why you would, wants the 20B token checkpoint reply and ill upload it as BananaMind 2.1 Pico EXP
Short version: we trained on 200B tokens (~222K:1 tokens-per-parameter). The model peaked at 20B tokens with an INT Index of 4.55, then degraded monotonically over the next 160B to 3.31 โ a 27% regression. Three of four Open SLM benchmarks were worse at the end of training than they were at 10% through.
The useful compute-optimal range for Pico-tier models looks like ~22Kโ30K tokens per parameter. Ratios like 7K:1, 15K:1, and 22K:1 all work fine โ TinyStories and most sub-3M community models sit in this range. Push much further and benchmarks start rotting.
Follow us for more:
@vovaRL
@Banaxi-Tech
Full writeup with all checkpoints, the Chinchilla-ratio control run, and the schedule-vs-overtraining analysis: https://huggingface.co/blog/Banaxi-Tech/ovdadadadd
And if anyone, i dont know the reason why you would, wants the 20B token checkpoint reply and ill upload it as BananaMind 2.1 Pico EXP
- 3 replies
posted an update 9 days ago
Post
1955
Random corporate secret of tonight:
Try overfitting a tiny model on billions of high-quality datapoints: you can't. You can do 100 epochs and see the model still improving.
You're welcome.
Try overfitting a tiny model on billions of high-quality datapoints: you can't. You can do 100 epochs and see the model still improving.
You're welcome.
- 1 reply
posted an update 10 days ago
Post
854
- GLM 5.2
- Flux 3
- New Qwen model
- New small model leaderboards
- Lots of people finetuning smol models.
- Some even under 12 year olds clauders are here (was not on my bingo card this year)
- ChatGPT's Sol became a lot faster this week
- LFM2.5 2.6b
- Kimi K3 (though only a few will run it)
- New Ling 3.0 Tiny
- New video model that is making south park videos?
- Deepseek v4 flash being more honest than bigger models
- The new model from meta
Everything Everywhere All At Once
- Flux 3
- New Qwen model
- New small model leaderboards
- Lots of people finetuning smol models.
- Some even under 12 year olds clauders are here (was not on my bingo card this year)
- ChatGPT's Sol became a lot faster this week
- LFM2.5 2.6b
- Kimi K3 (though only a few will run it)
- New Ling 3.0 Tiny
- New video model that is making south park videos?
- Deepseek v4 flash being more honest than bigger models
- The new model from meta
Everything Everywhere All At Once
- 1 reply
liked a
model 10 days ago