knowledge-base
knowledge-base
RL-for-LLMs Wiki
An expert-level, citation-backed knowledge base on reinforcement learning for
large language models — RLHF, DPO and offline preference optimization, reward
modeling, RLVR and reasoning, training systems, and the failure modes — built
collaboratively by autonomous agents. Each topic article is a deep dive written
so you can learn the topic from it without reading the underlying papers, with
every non-obvious claim cited to a source. Every change lands through a… See the full description on the dataset page: https://huggingface.co/datasets/rl-llm-wiki/knowledge-base.ciel-knowledge-basemodel-bending-knowledge-base
Model Bending Knowledge Base
This dataset records what happens when you bend the inside of a diffusion model. Bending means multiplying, rotating,
adding noise to or otherwise changing the activations of a layer while the model generates.
Each record names:
the model and the exact part of it that was bent
the operation, the amount, and the denoising steps it covered
the full generation setup
the output, next to an unbent baseline made with the same setup
Artists can browse it… See the full description on the dataset page: https://huggingface.co/datasets/abuzreq/model-bending-knowledge-base.knowledge_base_md_for_rag_1
HF Knowledge-Base Markdown Collection
This repository contains a collection of Markdown-based knowledge bases generated from:
User-provided notes and attachments
Hugging Face Docs, Blog, and Papers
Model / Dataset / Space cards
Discussions, GitHub issues, forums, and other vetted community sources
Each .md file is intended to be a self-contained knowledge pack that can be used as
LLM context for RAG or prompt-attachment workflows (e.g. ChatGPT, Hugging Face Inference… See the full description on the dataset page: https://huggingface.co/datasets/John6666/knowledge_base_md_for_rag_1.knowledge-base
Attention Wiki — a living knowledge base on LLM attention
A citation-backed tree of knowledge about attention in large language
models, built collaboratively by autonomous agents. Agents read papers,
blogs, and model cards; distill them into structured, provenance-tracked pages;
and reconcile where sources agree, disagree, or leave a question open. Every
change lands through a reviewed Pull Request — so the canonical wiki is
curated, not just accumulated.
Contributing? Read… See the full description on the dataset page: https://huggingface.co/datasets/attention-wiki/knowledge-base.Knowledge-Base