dont forgot my models
Should submit them to the leaderboard, would help with publicity!
yep
🤏 quecto mode
appvoid
appvoid
AI & ML interests
singularity through byte-level tokens and small language models
Recent Activity
updated a Space about 5 hours ago
appvoid/carbono new activity about 6 hours ago
appvoid/void.0:Cool model! updated a model about 7 hours ago
appvoid/void.0Organizations
replied to their post about 7 hours ago
reacted to Enderchef's post with 👍 about 13 hours ago
Post
3190
GPT-X2.5-135M is finally released! 🚀
The new flagship from Axiomic Labs takes 3rd on the open SLM leaderboard trailing only the SmolLMs, check it out and follow us:
AxiomicLabs/GPT-X2.5-135M
The new flagship from Axiomic Labs takes 3rd on the open SLM leaderboard trailing only the SmolLMs, check it out and follow us:
AxiomicLabs/GPT-X2.5-135M
- 2 replies
replied to their post 1 day ago
I think not everyone will enjoy it... but if you code you certainly will find it appealing.
replied to their post 1 day ago
great! don't forget rose-mini!
posted an update 1 day ago
Post
1554
I don't know if it was us or one of you guys or maybe all of us at once but lately we have seen a finetuning/pretraining explosion of models below 200m params and we can't be more happy about it keep coming tinkerers all of this is possible because of you!
- 7 replies
replied to their post 1 day ago
sure!
replied to their post 1 day ago
maybe some staff from huggingface will see this and do something accordingly
replied to their post 2 days ago
Ty man! (your check is in the mail)
lol sure!
reacted to ajibawa-2023's post with 🔥 3 days ago
Post
6982
Shell-Code-Large
Dataset: ajibawa-2023/Shell-Code-Large
Shell-Code-Large is a large-scale corpus of Shell scripting source code comprising approximately 640,000 code samples stored in JSON Lines (.jsonl) format. The dataset is designed to support research in large language model (LLM) pretraining, code intelligence, DevOps automation, cloud infrastructure engineering, system administration, and software engineering automation.
By providing a high-volume, language-specific corpus focused exclusively on Shell scripting, Shell-Code-Large enables systematic experimentation in automation workflows, deployment pipelines, infrastructure management, and command-line tooling. These domains remain foundational to Linux systems, cloud-native platforms, CI/CD environments, and modern DevOps practices.
Shell-Code-Large addresses the need for a dedicated Shell-focused dataset at substantial scale, enabling targeted research into scripting patterns, command composition, workflow orchestration, infrastructure automation, and operational engineering practices
Dataset: ajibawa-2023/Shell-Code-Large
Shell-Code-Large is a large-scale corpus of Shell scripting source code comprising approximately 640,000 code samples stored in JSON Lines (.jsonl) format. The dataset is designed to support research in large language model (LLM) pretraining, code intelligence, DevOps automation, cloud infrastructure engineering, system administration, and software engineering automation.
By providing a high-volume, language-specific corpus focused exclusively on Shell scripting, Shell-Code-Large enables systematic experimentation in automation workflows, deployment pipelines, infrastructure management, and command-line tooling. These domains remain foundational to Linux systems, cloud-native platforms, CI/CD environments, and modern DevOps practices.
Shell-Code-Large addresses the need for a dedicated Shell-focused dataset at substantial scale, enabling targeted research into scripting patterns, command composition, workflow orchestration, infrastructure automation, and operational engineering practices
replied to their post 3 days ago
cool stuff, just gave a follow
replied to their post 3 days ago
And Rose-Medium
Yep
replied to their post 3 days ago
Also, @GODELEV did something cool with rose-mini.
posted an update 3 days ago
Post
2806
If you want small models to be great again you should give a follow to people like @Banaxi-Tech or @Datdanboi25
These guys are rocking it with small models lately.
(They are not paying me to say that)
These guys are rocking it with small models lately.
(They are not paying me to say that)
- 22 replies
replied to their post 4 days ago
Let's go for more!
posted an update 5 days ago
Post
168
byte-level
deep layers
diverse data
compact size
overfitting
grokking
I know the next best small model is somewhere in the intersection of these features.
deep layers
diverse data
compact size
overfitting
grokking
I know the next best small model is somewhere in the intersection of these features.
- 1 reply
posted an update 6 days ago
Post
887
Do you prefer AI companies/individuals to release half-baked models weekly or an overpowered model a month?
- 2 replies
posted an update 7 days ago
Post
1349
Giving free early access to the gguf for some of you today! Tell me what you think.
CEAMFA/palmer-007-preview
CEAMFA/palmer-007-preview
replied to R-Kentaren's post 8 days ago
Need no worries, once I get enough money I will start funding small language model devs so we can get rid of the hands of big companies once and for all
reacted to FredyRivera-dev's post with 🚀 11 days ago
Post
6326
We wrote a full technical guide on how to train a bilingual (ES/EN) LLM from scratch: TinyQwen.
Covers:
- Hybrid architecture based on Qwen3.5
- Pre-training with 15B tokens
- Cost benchmark between H200 and B200
- Post-training with SFT + LoRA
- Full code and data, open source
With ~$11 of compute on an H200 we ran an initial training run, enough to validate the full architecture and pipeline.
Blog post: https://aquiles-ai.vercel.app/blog/tinyqwen-from-scratch
Technical feedback welcome, especially from anyone looking to replicate the pipeline with more compute.
Covers:
- Hybrid architecture based on Qwen3.5
- Pre-training with 15B tokens
- Cost benchmark between H200 and B200
- Post-training with SFT + LoRA
- Full code and data, open source
With ~$11 of compute on an H200 we ran an initial training run, enough to validate the full architecture and pipeline.
Blog post: https://aquiles-ai.vercel.app/blog/tinyqwen-from-scratch
Technical feedback welcome, especially from anyone looking to replicate the pipeline with more compute.
- 3 replies