Skills

All Skills

Model Compression

Skills tagged with #Model Compression

@plasmate-labs
MCP

Io.Github.Plasmate Labs/Plasmate

Agent-native headless browser. HTML in, Semantic Object Model out. 10x token compression.

mcpgithubbrowser
plasmate-labs/plasmate
6mo ago
0
@Orchestra-Research

awq-quantization

Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.

OptimizationAWQQuantization4-BitActivation-AwareMemory Optimization
Orchestra-Research/AI-research-SKILLs+46 more
6mo ago
5.0K0
@gavdalf

total-recall

The only memory skill that watches on its own. No database. No vectors. No manual saves. Just an LLM observer that compresses your conversations into prioritised notes, consolidates when they grow, and recovers anything missed. Five layers of redundancy, zero maintenance. ~$0.00/month (using free-tier models). While other memory skills ask you to remember to remember, this one just pays attention.

gavdalf/total-recall
6mo ago
2030
@headroomlabs-ai

headroom

Use when a Python or TypeScript app sends large tool outputs, logs, JSON, search results or long chat history to an LLM and the task is to cut input tokens, reduce token cost, fit a context window, or trim tool results without losing errors. Adds the headroom-ai compress() call; in-process, no API key, no model download.

headroomlabs-ai/headroom
4h ago
79.0K0
@huguryildiz

ieee-acm-paper-writing

Draft, rewrite, compress, structure, calibrate, humanize, or audit engineering manuscripts for IEEE and ACM Transactions, journals, and conferences, with optional self-contained HTML audit maps and script-checked claim ledgers. Use for abstracts, introductions, related work, system models, mathematical formulations, algorithms, experimental methods, results, discussions, conclusions, contribution lists, notation and claim audits, evidence-grounded peer-review reports, venue adaptation, machine-idiom humanization of AI-flavored prose, or landmark-paper calibration in communications, signal processing, energy systems, robotics, optimization, simulation, ML-assisted engineering, and computer systems. Do not use for general documentation, grant proposals, marketing copy, or editorial accept/reject advocacy detached from manuscript evidence.

huguryildiz/ieee-acm-paper-writing
8h ago
130