README
🚀
AI & ML interests
None defined yet.
Recent Activity
View all activity
Hoglet-33
updated a
Space 7 days ago
Post
6267
Introducing VOID. A new research branch of basically AI.
VOID — Verification of Objectives, Intentions, and Deception.
We study what lies beneath the surface: objectives, intentions, and the possibility of deception in AI systems.
There isn't much to see yet.
That will change.
Follow us for updates:
@Hoglet-33
void-research
basically-ai
VOID — Verification of Objectives, Intentions, and Deception.
We study what lies beneath the surface: objectives, intentions, and the possibility of deception in AI systems.
There isn't much to see yet.
That will change.
Follow us for updates:
@Hoglet-33
- 7 replies
i64systems
posted an update 16 days ago
Post
84
we taught a small model to predict how simulated fluid would move eight steps into the future. it learned from examples, then succeeded on examples withheld from training.
two things mattered:
- its memory helped. the version with an internal memory produced about 41–45% less prediction error than the comparison model using recent observations.
- the learning was repeatable. restarting training reproduced every recorded update and saved checkpoint exactly. resuming halfway through also produced the same ending.
that gives us working evidence that bf16 gpu training can learn and remain exactly repeatable on this 3090 ti and software setup.
thank you for your time.
two things mattered:
- its memory helped. the version with an internal memory produced about 41–45% less prediction error than the comparison model using recent observations.
- the learning was repeatable. restarting training reproduced every recorded update and saved checkpoint exactly. resuming halfway through also produced the same ending.
that gives us working evidence that bf16 gpu training can learn and remain exactly repeatable on this 3090 ti and software setup.
thank you for your time.
i64systems
posted an update 17 days ago
Post
98
little bob’s updated weights now change his actions in doom. all three fresh replays matched exactly
yes i am training my bf16/fp32 non-language models weights with replayable inference *in doom*
yes i am training my bf16/fp32 non-language models weights with replayable inference *in doom*
Post
3213
Today, we planned to release Pebble-50M and Pebble-50M-Chat to the world. Unfortunately, due to a few issues, that didn't go quite as planned.
What happened:
- Some data and benchmark results were lost or corrupted
- The models performed worse on benchmarks than our other Pebble models
Despite that, you can still find both models here:
Pebble-50M-beta: basically-experimental/Pebble-50M-beta
Pebble-50M-Chat-beta: basically-experimental/Pebble-50M-Chat-beta
There are still some interesting improvements in these models:
- Compatible with non-CUDA devices
- Vocabulary increased to 16K tokens
- Context length increased to 16K tokens
For now, there won't be any more Pebble releases for a while. We're going to take some time to experiment with other approaches and hopefully make the next generation a monumental leap over this one.
Follow for updates:
@Hoglet-33
basically-ai
basically-experimental
What happened:
- Some data and benchmark results were lost or corrupted
- The models performed worse on benchmarks than our other Pebble models
Despite that, you can still find both models here:
Pebble-50M-beta: basically-experimental/Pebble-50M-beta
Pebble-50M-Chat-beta: basically-experimental/Pebble-50M-Chat-beta
There are still some interesting improvements in these models:
- Compatible with non-CUDA devices
- Vocabulary increased to 16K tokens
- Context length increased to 16K tokens
For now, there won't be any more Pebble releases for a while. We're going to take some time to experiment with other approaches and hopefully make the next generation a monumental leap over this one.
Follow for updates:
@Hoglet-33
- 4 replies
Hoglet-33
published 2
models 18 days ago
i64systems
posted an update 20 days ago
Post
76
NOW UPDATED ❗❗
openbob 5.0.1🐭🔎
An integer execution method for reproducible inference from publicly available model weights, demonstrated on Qwen3-4B. Journaled bytes and all.
Keep an eye out for the gpt-oss-120B on the 24gb GPU- deterministically.
We make AI models do the same things every time!⛓️😈
i64systems/Qwen3-4B-openbob-i8
openbob 5.0.1🐭🔎
An integer execution method for reproducible inference from publicly available model weights, demonstrated on Qwen3-4B. Journaled bytes and all.
Keep an eye out for the gpt-oss-120B on the 24gb GPU- deterministically.
We make AI models do the same things every time!⛓️😈
i64systems/Qwen3-4B-openbob-i8
Post
3444
Pebble-25M and Pebble-25M-Chat are out now!
We’re excited to release Pebble-25M and Pebble-25M-Chat!
Both models use our 3:1 Mamba2/Transformer hybrid architecture and were pretrained on 25B tokens. Pebble-25M-Chat was then further fine-tuned on an additional 250M tokens from smol-smoltalk, following the same approach used for the Pebble-10M models.
We hope you enjoy experimenting with them!
Pebble-50M is coming in a few days.
Models
Pebble-25M: basically-ai/Pebble-25M
Pebble-25M-Chat: basically-ai/Pebble-25M-Chat
Pebble-10M GGUFs
In case you missed it, our friend @ContextReq made GGUF versions of the Pebble-10M models:
https://huggingface.co/ContextReq/Pebble-10M-GGUF
https://huggingface.co/ContextReq/Pebble-10M-Chat-GGUF
Follow us if you don’t want to miss future releases and updates!
@Hoglet-33
basically-ai
basically-experimental
We’re excited to release Pebble-25M and Pebble-25M-Chat!
Both models use our 3:1 Mamba2/Transformer hybrid architecture and were pretrained on 25B tokens. Pebble-25M-Chat was then further fine-tuned on an additional 250M tokens from smol-smoltalk, following the same approach used for the Pebble-10M models.
We hope you enjoy experimenting with them!
Pebble-50M is coming in a few days.
Models
Pebble-25M: basically-ai/Pebble-25M
Pebble-25M-Chat: basically-ai/Pebble-25M-Chat
Pebble-10M GGUFs
In case you missed it, our friend @ContextReq made GGUF versions of the Pebble-10M models:
https://huggingface.co/ContextReq/Pebble-10M-GGUF
https://huggingface.co/ContextReq/Pebble-10M-Chat-GGUF
Follow us if you don’t want to miss future releases and updates!
@Hoglet-33
- 7 replies
i64systems
posted an update 22 days ago
Post
97
remat is no longer a one-model claim!!proved it on Qwen3-30B-A3B, K=32 of 128 experts resident, output task byte-identical to the full reference, zero bytes different *in bf16*🥰🥰 GPU comes next😈
- 6 replies
Post
3314
Pebble 10M and Pebble 10M Chat are now released!
Both models use our Mamba/Transformer 3:1 hybrid architecture and were pretrained on 25 billion tokens.
Pebble 10M Chat was additionally fine-tuned on 250 million tokens of Smol-SmolTalk to improve its conversational capabilities.
You can find them here:
- basically-ai/Pebble-10M
- basically-ai/Pebble-10M-Chat
We hope you enjoy using them. The rest of the Pebble family will be released soon.
Follow for more:
@Hoglet-33
basically-ai
Both models use our Mamba/Transformer 3:1 hybrid architecture and were pretrained on 25 billion tokens.
Pebble 10M Chat was additionally fine-tuned on 250 million tokens of Smol-SmolTalk to improve its conversational capabilities.
You can find them here:
- basically-ai/Pebble-10M
- basically-ai/Pebble-10M-Chat
We hope you enjoy using them. The rest of the Pebble family will be released soon.
Follow for more:
@Hoglet-33
- 32 replies
Post
3076
We are announcing the first generation of the Pebble model family!
These are the models we are releasing:
- Pebble 10M
- Pebble 25M
- Pebble 50M
Each model will use a Mamba-Transformer 3:1 hybrid architecture and will be pretrained on 25 billion tokens before IFT and SFT.
Depending on development time and resources, we may also release:
- Pebble 5M
- Pebble 75M
- Pebble 1M (possibly)
We hope you're excited and enjoy the models!
Follow for more:
@Hoglet-33
basically-ai
These are the models we are releasing:
- Pebble 10M
- Pebble 25M
- Pebble 50M
Each model will use a Mamba-Transformer 3:1 hybrid architecture and will be pretrained on 25 billion tokens before IFT and SFT.
Depending on development time and resources, we may also release:
- Pebble 5M
- Pebble 75M
- Pebble 1M (possibly)
We hope you're excited and enjoy the models!
Follow for more:
@Hoglet-33
- 7 replies