6 posts
TrustformeRS 0.2.0 gives CUDA the same device-resident attention pipeline Metal already had, adds batched CUDA matmul and refcounted GPU buffers, fixes a silent CUDA data race, and drops the torch/libtorch backend workspace-wide. The sovereign transformer layer for the COOLJAPAN ecosystem.
TrustformeRS 0.1.4 migrates CUDA and Metal from cudarc/scirs2-MPS to the Pure-Rust oxicuda stack, passes 12/12 CPU↔CUDA parity tests on a real RTX A4000, ships real PyRwkvModel/PyMambaModel classes on PyO3 0.28, and goes unwrap()-free workspace-wide. The sovereign transformer layer for the COOLJAPAN ecosystem.
TrustformeRS 0.1.3 patch — real SHAP/LIME/Integrated-Gradients interpretability, ZeroCopyTensorView + GlobalMemoryPool + GlobalProfiler, Miri-verified memory-pool fixes, real SHA-256 on the HuggingFace upload path, and real OOXML .xlsx export via oxiarc-archive.
TrustformeRS 0.1.2 patch — full Kubernetes/ACI/OpenShift deploy manifests, EnhancedProfiler exports (Flamegraph/OTLP/Jaeger), scaled-dot-product attention kernel fusion, NMS + token-classification pipelines, Q2_K/Q3_K GGUF quant; the stub-only TPU backend is removed for honesty.
TrustformeRS 0.1.1 patch — 22 new transformer architectures (49+ total: Falcon2, Gemma2, Mamba2, Qwen2.5, Phi4, Whisper, StarCoder2, xLSTM, and more). ONNX Runtime replaced by Pure Rust oxionnx, tar replaced by oxiarc-archive, Kafka feature-gated. Load any architecture through one AutoModel call — no Python, no PyTorch, no C++ ONNX runtime.
Pure Rust Hugging Face Transformers — the first stable release. 27+ transformer architectures, 17x CPU BLAS acceleration, GGUF/AWQ/GPTQ quantization, and WASM + server + mobile deployment. No Python, no PyTorch.