--- license: mit library_name: mlx tags: [mlx, knowledge-editing, retrieval, synthetic-data] --- # Hemispheres: step-1 checkpoints Weights for the step-1 synthetic-world runs of Hemispheres, a language model that keeps its knowledge in a separate, editable store and reads it inside the forward pass. Each run directory holds `config.json` (every training flag, seed and model shape) and MLX safetensors checkpoints. The run records (metrics, per-question evaluation outputs, data fingerprints), the comparison report and the code to load and evaluate these weights are in the project repository, under `results/step1/`. | run | arm | params | checkpoints | sha256 | |---|---|---|---|---| | `context-a` | context | 25.5M | `final`, `latest` | `ae48aaa6bc50` | | `context-multi-bios` | context | 25.5M | `final`, `latest` | `8d97615b89a9` | | `context-multi-bios-20k` | context | 25.5M | `final`, `latest` | `11424cc903c9` | | `context-multi-bios-20k-s1` | context | 25.5M | `final`, `latest` | `4e9410c97d16` | | `dense-a` | dense | 25.5M | `final`, `latest` | `81e8eb4ac912` | | `dense-a-k100` | dense | 25.5M | `final`, `latest` | `c2535e281e08` | | `dense-a-to-b` | dense | 25.5M | `final`, `latest` | `17c630e69033` | | `latent-a` | latent | 29.2M | `final`, `latest` | `f4f3b1fbe96a` | | `latent-a-all` | latent | 29.2M | `final`, `latest` | `57dc7d12714c` | | `latent-multi` | latent | 29.2M | `final`, `latest` | `1b2490e51d93` | | `latent-multi-nohop` | latent | 29.2M | `latest` | `dc2494c38336` | | `lookup-a` | lookup | 25.5M | `final`, `latest` | `e06385a28712` | ```sh pip install -e '.[hub]' python -m hemispheres.records fetch latent-multi # into runs/latent-multi/, sha256-checked python -m hemispheres.synth.build --name world-b --index 1 --edits 1,100,1000 python -m hemispheres.evaluate --run runs/latent-multi --data data/world-b --sets all --n 300 ``` Models are 25.5M (dense, lookup, context) or 29.2M (latent) parameters, fp32, trained from scratch on generated worlds. They are research artifacts for the synthetic task, not general-purpose language models. Released under the MIT license (see `LICENSE`).