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Complete CPU GGUF serving + docs + minimal UI redesign
Serving: - Serve fine-tuned Phi-3 as a 4-bit Q4_K_M GGUF via llama.cpp (source-built llama-cpp-python 0.3.19); cap n_threads to the container's vCPU count. - Dockerfile builds llama-cpp-python from source against glibc (prebuilt wheels are musl-only for phi3-capable versions) with single-threaded compile to avoid build OOM. Frontend: - Redesign the web UI as a flat, minimal layout (no gradients/glass/glow), with a project stats panel, schema row counts, and an on-page FAQ. - Remove the unreliable base-model comparison; single fine-tuned result with a wall-clock timer and an accurate CPU banner. Docs + eval: - Add fine-tuning + quantization + deployment blog and HF model cards (docs/). - Add the execution-accuracy eval harness (scripts/eval_execution_accuracy.py). - Update repo README to reflect GGUF/CPU serving. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>1d8be28
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Revert "Migrate CPU serving to llama.cpp + Q5_K_M GGUF (was bf16 transformers)"
This reverts commit 564ad28ca5effbb5f2390da477c1915c03fbc8ad.d031aeb -
Revert "Make torch/transformers/peft lazy imports so CPU Space boots without them"
This reverts commit eac26c792828354a0af21d78d763b0320eb0d2b2.2f03b0e -
Make torch/transformers/peft lazy imports so CPU Space boots without them
eac26c7 -
Migrate CPU serving to llama.cpp + Q5_K_M GGUF (was bf16 transformers)
564ad28 -
Fix bugs
52e3716 -
Update CPU warning banner with accurate load and query times
e4ff54d -
Fix inference device bug, auto-load model, remove fine-tuning console, UI cleanup
f5ce94d -
initial deployment
55159b1