Entwickler-Tools
ms-swift
Fine-tune and deploy 600+ LLMs and 300+ multimodal models with PEFT or full-parameter training.
★ 15,8 Tsd. SterneApache-2.0
Anleitung ansehen →peft ist ein Open-Source-Projekt aus der Kategorie Entwickler-Tools von huggingface (huggingface/peft auf GitHub). Es hat 21.769 Sterne auf GitHub und 2.560 Forks, wird unter der Lizenz Apache-2.0 veröffentlicht und wurde zuletzt am 8. Oktober 2026 auf GitHub aktualisiert.
Fine-tune huge models on small hardware with LoRA and other efficient methods
Pick the model to adapt and a method such as LoRA that fits your memory budget.
Install the peft package from PyPI - cloning is only needed to work on the library itself.
Wrap your model with a PEFT config (for example LoraConfig) using the README quickstart.
Train on your dataset, check the trainable-parameter count, and save the small adapter.
Implements LoRA and a family of parameter-efficient methods behind one consistent API.
The README's example trains about 0.12% of a 3B model's parameters with LoRA instead of the full model.
Use PEFT models directly through the Transformers integration for training and inference.
Apply parameter-efficient tuning to diffusion models as well as language models.
Works with Accelerate for distributed/offloaded training and with TRL for RLHF-style workflows.
Combines with quantization so large models can be adapted on modest GPUs.
Get the source code from GitHub and enter the project directory.
git clone https://github.com/huggingface/peft.git
cd peftInstall from PyPI alongside Transformers and Accelerate.
pip install peftThe README quickstart loads a model, applies a LoraConfig, and prints the trainable parameter share.
from peft import LoraConfig, get_peft_model
# load a model, then:
# model = get_peft_model(model, LoraConfig(...)) - see README quickstartIt is maintained by Hugging Face and contributors on GitHub.
Yes - PEFT is Apache-2.0 licensed and free to use. Base models you adapt carry their own licenses.
No API key is needed: training and inference run locally on your hardware with open models.
Compared with full fine-tuning, PEFT trains a fraction of the parameters (often well under 1%), cutting compute and storage; compared with prompt-only methods, it actually updates model behavior.
Run pip install peft and follow the README Quickstart to wrap a model with LoRA and print its trainable parameters.
Fine-tune and deploy 600+ LLMs and 300+ multimodal models with PEFT or full-parameter training.
Unified, efficient fine-tuning of 100+ LLMs and VLMs with a CLI and Web UI — ACL 2024
A coding-agent harness optimized for smaller local LLMs — small models, serious coding work
MCPJam Inspector: chat with, inspect, debug, and evaluate MCP servers across clients and models.
A free course to get into large language models, with roadmaps and runnable Colab notebooks
Hugging Face's library for loading and processing datasets for AI models in one line
Die anderen Projekte der Kategorie Entwickler-Tools mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls peft nicht das Richtige ist.
The open source coding agent
The model-definition framework behind modern AI — thousands of pretrained transformers for text, vision, and audio.
Anthropic's agentic coding tool that lives in your terminal and works across your whole codebase
Cross-platform desktop all-in-one manager for Claude Code, Codex, OpenCode and other coding agents
OpenAI's lightweight coding agent that runs locally in your terminal
Verwandte Projekte der Kategorie Entwickler-Tools im Katalog, die peft bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.
Hugging Face's library for loading and processing datasets for AI models in one line
Reverse engineer anything with agents - from app behavior down to native binaries
A desktop GUI and toolkit for Claude Code - agents, sessions, analytics and MCP
Self-hosted TikTok and Douyin scraper API - no-watermark downloads, MCP and web console
A 25MB database client for 100+ databases — with a built-in AI assistant, MCP server and CLI
A high-performance coding agent harness in Rust - fast TUI, swarms and every provider
Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.