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Training progress: - Show row counts in status messages: "Loaded dataset from HuggingFace: Open-Orca/OpenOrca (4,233,923 rows)" instead of just the dataset name - Emit "Formatting dataset (N rows)..." and "Applying chat template (N rows)..." status updates so users see progress during the preprocessing stages that previously appeared stuck Deferred llama.cpp compilation: - Add LlamaCppBuilder that runs cmake build in a background thread at server startup if the llama-server binary is missing - Studio starts immediately and is usable for training/non-GGUF tasks while llama.cpp compiles in the background - GGUF model loads wait for the build to finish with a helpful message - Add /api/inference/llama-cpp-status endpoint for build status - Frontend shows "Waiting for llama.cpp to compile..." toast when loading a GGUF while build is in progress |
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| .. | ||
| assets | ||
| auth | ||
| core | ||
| loggers | ||
| models | ||
| plugins | ||
| requirements | ||
| routes | ||
| state | ||
| tests | ||
| utils | ||
| __init__.py | ||
| colab.py | ||
| main.py | ||
| run.py | ||