Small, calibrated decision models on your own machine: systemone-compatible local server, 6 agent skills, Claude Code guard, MCP tools. Weights on Hugging Face.
alphaparkinc/genpark-speculative-decoding-draft-acceptance-evaluator-skillGenPark AI Agent Skill - Rejection sampling and logit verification engine for speculative decoding acceleration.
Alpha-Park/genpark-paged-attention-kv-cache-block-allocator-skillGenPark AI Agent Skill - Simulates vLLM PagedAttention non-contiguous virtual memory block table allocation for dynamic KV-cache management.
alphaparkinc/genpark-multi-gpu-tensor-parallel-sharding-planner-skillGenPark AI Agent Skill - Calculates tensor parallelism column and row weight matrix partition splits across distributed GPU clusters.
Alpha-Park/genpark-speculative-decoding-draft-acceptance-evaluator-skillGenPark AI Agent Skill - Rejection sampling and logit verification engine for speculative decoding acceleration.
alphaparkinc/genpark-gguf-tensor-metadata-header-validator-skillGenPark AI Agent Skill - Validates GGUF/GGML model binary headers, tensor alignment, KV-cache parameters and architecture keys.
Alpha-Park/genpark-weight-quantization-kquants-block-packer-skillGenPark AI Agent Skill - Simulates k-quants block compression (Q4_K_M, Q8_0) packing FP16 weights into quantized blocks with scale factors.
Alpha-Park/genpark-multi-gpu-tensor-parallel-sharding-planner-skillGenPark AI Agent Skill - Calculates tensor parallelism column and row weight matrix partition splits across distributed GPU clusters.
alphaparkinc/genpark-weight-quantization-kquants-block-packer-skillGenPark AI Agent Skill - Simulates k-quants block compression (Q4_K_M, Q8_0) packing FP16 weights into quantized blocks with scale factors.
alphaparkinc/genpark-paged-attention-kv-cache-block-allocator-skillGenPark AI Agent Skill - Simulates vLLM PagedAttention non-contiguous virtual memory block table allocation for dynamic KV-cache management.
Alpha-Park/genpark-gguf-tensor-metadata-header-validator-skillGenPark AI Agent Skill - Validates GGUF/GGML model binary headers, tensor alignment, KV-cache parameters and architecture keys.