# hiyouga/FastEdit

🩹Editing large language models within 10 seconds⚡

Repository: https://github.com/hiyouga/FastEdit
Canonical: https://ross.abutalabs.com/products/fastedit
Language: Python
License: Apache-2.0
License Family: permissive
Topics: llms, chatgpt, gpt, llama, transformers, large-language-models, chatbots, bloom, falcon, pytorch
Last push: 2023-08-13T03:52:25+00:00

## Health v2 (maintenance only)
Score: 19/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 82
- inputs: {"age_days": 1151, "days_push": 1116, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1366, forks 103 (observed 2026-08-28T04:04:31.263384+00:00)

## What it is
FastEdit is a Python library and CLI tool for editing large language models, injecting fresh or customized factual knowledge into pretrained models in seconds using the Rank-One Model Editing (ROME) algorithm. It supports models such as GPT-J, LLaMA/LLaMA-2, BLOOM, Falcon, Baichuan, and InternLM via Hugging Face Transformers.

## Use cases
- inject new facts into a llama model without retraining
- update outdated knowledge in a large language model
- edit a model's answer to a factual question
- quickly patch factual errors in an llm
- run rank-one model editing on gpt-j or falcon
- customize chatbot knowledge with a single command

## When to choose
- you need to update specific factual knowledge in an open-source LLM without full fine-tuning
- you want a fast, single-command model editing workflow with ROME
- you work with supported architectures like LLaMA, BLOOM, Falcon, or Baichuan and have a 24GB+ GPU

## When to avoid
- you need broad capability changes rather than targeted factual edits
- you require frequent large-scale knowledge updates, which fine-tuning or RAG handles better
- your model architecture is not among the supported ones
- you need actively developed tooling, as the project has seen limited recent releases

## Facets
- artifact type: library
- maturity: maintenance
- function: llm-training, machine-learning, cli
- domain: large-language-models, machine-learning
- platform: python
- tags: model-editing, knowledge-injection, rome, transformers, pytorch, llama, factual-editing, natural-language-processing, gpu, linux, macos

## Member repositories
- hiyouga/FastEdit (main) score 19

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:31.263384+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:41:12.557879+00:00, confidence not recorded.
  - readme: https://github.com/hiyouga/FastEdit (fetched 2026-08-28T04:04:31.263384+00:00, sha 71ed342d6a83)
- Data as of 2026-08-30T08:39:29.467469+00:00.