cactus-compute/needle
Automation foundation model for tiny devices: 2-bit, 8-29 MB, tool calls, ASR, structured extraction and embeddings on phones, wearables, smart homes, robots, cars and microcontrollers.
Doing simple retrieval from LLM models at various context lengths to measure accuracy
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Latest capture 2026-10-17 03:16
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Automation foundation model for tiny devices: 2-bit, 8-29 MB, tool calls, ASR, structured extraction and embeddings on phones, wearables, smart homes, robots, cars and microcontrollers.
Benchmark for tracking model capability after release.
The simplest, fastest repository for training/finetuning medium-sized GPTs.
a recursive self-improving harness designed to help your agents (and future iterations of those agents) succeed on any task
Open-source text humanization pipeline with every intermediate step published. Two LLM rewrites at temp 1.3, then two hops across different NMT engines. Four documented methodologies you can read, modify, and run locally.
Anti-laziness skill for AI agents. Core: the Depth Tree method, which splits a task N layers deep and gives every leaf the full time budget of the whole task, so effort multiplies with depth. Grounded in 2025-2026 research on model laziness, underthinking and premature completion.