neuron-explorer
Steering-first neuron explorer for Qwen3.5-4B: push every MLP neuron, keep every rollout, browse the results
An inference engine written in Rust for GGUF, AWQ, and FP8 (W8A8) checkpoints, with hand-written CUDA and Metal kernels.
Developer toolsRust · CudaGitHub @jackwangfengOnlineOwner unconfirmed
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An inference engine written in Rust for GGUF, AWQ, and FP8 (W8A8) checkpoints, with hand-written CUDA and Metal kernels — no PyTorch, no libtorch, no ggml
Taken from the repository README
Loading the full README. The saved excerpt is shown below.
An inference engine written in Rust for GGUF, AWQ, native FP8 (W8A8), and
native NVFP4 (W4A4) checkpoints, with hand-written kernels for both NVIDIA
(CUDA) and Apple Silicon (Metal) GPUs — no PyTorch, no libtorch, no ggml.
CUDA is the primary, most complete backend; Metal covers dense decode, GQA
attention and GatedDeltaNet today, with MoE, the vision tower, and the
INT4/FP8/NVFP4 tensor-core GEMM paths still CUDA-only (see
Metal below). The whole path from a model
checkpoint on disk to an OpenAI-compatible HTTP response is in this
repository.Read the full README ↗The full README is unavailable right now. Read it at the original link. The saved excerpt is shown below.
An inference engine written in Rust for GGUF, AWQ, native FP8 (W8A8), and
native NVFP4 (W4A4) checkpoints, with hand-written kernels for both NVIDIA
(CUDA) and Apple Silicon (Metal) GPUs — no PyTorch, no libtorch, no ggml.
CUDA is the primary, most complete backend; Metal covers dense decode, GQA
attention and GatedDeltaNet today, with MoE, the vision tower, and the
INT4/FP8/NVFP4 tensor-core GEMM paths still CUDA-only (see
Metal below). The whole path from a model
checkpoint on disk to an OpenAI-compatible HTTP response is in this
repository.Read the full README ↗