| --- |
| library_name: safetensors |
| tags: |
| - mamba |
| - sequence-model |
| - strategy-game |
| - 4x |
| license: other |
| --- |
| |
| # 4X Mamba |
|
|
| Legacy public 4X strategy-game Mamba checkpoint. |
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|
| This is the first model: a pretrained Mamba2-style sequence model trained with a next-token prediction objective over synthetic 4X strategy-game traces. It is kept as a reference checkpoint, not as the current latent world model. |
|
|
| The repository has been cleaned so the public artifact is weights-only: |
|
|
| - `model.safetensors` - model weights only |
| - `config.json` - minimal model/checkpoint metadata |
|
|
| No optimizer state, scheduler state, training corpus, simulator source, infrastructure scripts, benchmark harness, or unrelated project files are included in the cleaned artifact. |
|
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| Clean public code for the current world model lives here: |
|
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| https://github.com/ProjectAI00/4x-mamba |
|
|
| ## Model |
|
|
| - Architecture: legacy Mamba2-style sequence model |
| - Objective: next-token prediction |
| - Parameters: `27,648,512` |
| - Original training metadata: |
| - Global step: `47,500` |
| - Epoch: `3` |
| - Validation loss: `0.7532` |
| - Validation accuracy: `0.8130` |
|
|
| The current latent transition world model is published separately at `aimar00/4x-mamba-world-model`. |
|
|
