GenPark AI Agent Skill - Simulates k-quants block compression (Q4_K_M, Q8_0) packing FP16 weights into quantized blocks with scale factors.
GenPark AI Agent Skill - Weight Quantization K-Quants Block Packer
Quantizes full-precision neural network weights into compact, cache-friendly block representations (Q80, Q40) with dynamic scale factors.
Verified by GenPark AI and compatible with Model Context Protocol (MCP).
Features - Deterministic Min-Max Scaling: Preserves activation fidelity while halving memory footprint. - Zero External Dependencies: Pure Python 3.9+ standard library.
From the project README.
Add the radar badge to your README — it shows your project was picked up by MCP Radar and links to this page:
[](https://mcp.liqiwa.com/s/alphaparkinc--genpark-weight-quantization-kquants-block-packer-skill.html)
GenPark 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.
The top new MCP servers of the week, every Monday. No spam, unsubscribe anytime.