The latent cache holds two fp32 posterior tensors per crop/flip variant per image, pinned on CUDA hosts, so datasets with thousands of images can exhaust host or pinned memory with no fallback. Estimate the cache size from the first real encoded latent and fall back to per-step VAE encoding when it exceeds a 4 GiB budget. UNSLOTH_DIFFUSION_FORCE_LATENT_CACHE bypasses the gate; the existing UNSLOTH_DIFFUSION_NO_LATENT_CACHE opt-out is unchanged. |
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| .. | ||
| backend | ||
| frontend | ||
| src-tauri | ||
| __init__.py | ||
| install_llama_prebuilt.py | ||
| install_node_prebuilt.py | ||
| install_python_stack.py | ||
| install_sd_cpp_prebuilt.py | ||
| LICENSE.AGPL-3.0 | ||
| node_prebuilt_pins.json | ||
| package-lock.json | ||
| package.json | ||
| setup.bat | ||
| setup.ps1 | ||
| setup.sh | ||
| Unsloth_Studio_Colab.ipynb | ||