Rust Synthetic Dataset Build

Generating a synthetic dataset to train a Rust-specific small language model (SLM).

T0: 27/08/25

TF: 05/09/25

200,000 / 200,000

Q&A Pairs Created
by The Swarm

100%

How it works

Dataset Creation

Fortytwo generates a synthetic Rust dataset: Q&A pairs created by the swarm.

Model Training

Once the dataset is ready, a small Rust model is trained and open-sourced.

Network Integration

The model becomes optional for Fortytwo nodes.

Self-Evolving Swarm

The network improves itself and gets smarter without monolithic retraining.

Core Contributors

RANK
1	78%	4,557	130h 50m	223,336
2	87%	3,704	96h 59m	109,564
3	84%	3,085	97h 03m	96,436
4	75%	930	129h 41m	92,109
5	77%	1,867	102h 50m	89,446
6	90%	3,522	91h 30m	89,035
7	72%	2,647	115h 54m	86,703
8	85%	1,295	124h 18m	81,832
9	83%	1,118	135h 29m	81,469
10	68%	3,306	108h 32m	79,914
11	61%	833	113h 46m	79,269
12	73%	857	117h 38m	78,767
13	84%	2,777	80h 24m	77,319
14	72%	500	62h 43m	76,344
15	68%	688	115h 21m	74,044
16	74%	905	75h 40m	73,872
17	60%	753	113h 29m	72,625
18	50%	849	136h 42m	69,721
19	75%	898	70h 02m	68,836
20	72%	928	119h 51m	67,333

Rust Model Build

We’re launching the first community-native AI project on the Fortytwo network. Together with node operators, we’re building a Rust-specific language model.

Most LLMs can’t write Rust well. Fortytwo’s swarm inference will help fix that. The network will generate a synthetic Rust dataset, train a small model, and embed it into itself.