Statistics for topic lora

Unify Efficient Fine-Tuning of 100+ LLMs

Finetune Llama 3, Mistral, Phi & Gemma LLMs 2-5x faster with 80% less memory

《开源大模型食用指南》基于Linux环境快速部署开源大模型，更适合中国宝宝的部署教程

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

ms-swift: Use PEFT or Full-parameter to finetune 250+ LLMs or 25+ MLLMs

[ICML2024] Official PyTorch implementation of DoRA: Weight-Decomposed Low-Rank Adaptation

ms-swift: Use PEFT or Full-parameter to finetune 250+ LLMs or 25+ MLLMs

《开源大模型食用指南》基于Linux环境快速部署开源大模型，更适合中国宝宝的部署教程

A Meshtastic desktop client, allowing simple, offline deployment and administration of an ad-hoc mesh communication network. Built in Rust and TypeScript.

Utility for Safetensors Files

Unify Efficient Fine-Tuning of 100+ LLMs

Finetune Llama 3, Mistral, Phi & Gemma LLMs 2-5x faster with 80% less memory

《开源大模型食用指南》基于Linux环境快速部署开源大模型，更适合中国宝宝的部署教程

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

ms-swift: Use PEFT or Full-parameter to finetune 250+ LLMs or 25+ MLLMs

[ICML2024] Official PyTorch implementation of DoRA: Weight-Decomposed Low-Rank Adaptation

AutoAudit—— the LLM for Cyber Security 网络安全大语言模型

ms-swift: Use PEFT or Full-parameter to finetune 250+ LLMs or 25+ MLLMs

Finetune Llama 3, Mistral, Phi & Gemma LLMs 2-5x faster with 80% less memory

《开源大模型食用指南》基于Linux环境快速部署开源大模型，更适合中国宝宝的部署教程

Unify Efficient Fine-Tuning of 100+ LLMs

Finetune Llama 3, Mistral, Phi & Gemma LLMs 2-5x faster with 80% less memory

《开源大模型食用指南》基于Linux环境快速部署开源大模型，更适合中国宝宝的部署教程

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

ms-swift: Use PEFT or Full-parameter to finetune 250+ LLMs or 25+ MLLMs

[ICML2024] Official PyTorch implementation of DoRA: Weight-Decomposed Low-Rank Adaptation

Code for NOLA, an implementation of "nola: Compressing LoRA using Linear Combination of Random Basis"

对llama3进行全参微调、lora微调以及qlora微调。

Give your computer an AI Brain

A map of all Meshtastic nodes heard via MQTT.

Finetune Llama 3, Mistral, Phi & Gemma LLMs 2-5x faster with 80% less memory

《开源大模型食用指南》基于Linux环境快速部署开源大模型，更适合中国宝宝的部署教程

33B Chinese LLM, DPO QLORA, 100K context, AirLLM 70B inference with single 4GB GPU

Code and documents of LongLoRA and LongAlpaca (ICLR 2024 Oral)

ms-swift: Use PEFT or Full-parameter to finetune 250+ LLMs or 25+ MLLMs

Unify Efficient Fine-Tuning of 100+ LLMs

Finetune Llama 3, Mistral, Phi & Gemma LLMs 2-5x faster with 80% less memory

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)

Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"

Finetune Llama 3, Mistral, Phi & Gemma LLMs 2-5x faster with 80% less memory

雅意大模型：为客户打造安全可靠的专属大模型，基于大规模中英文多领域指令数据训练的 LlaMA 2 & BLOOM 系列模型，由中科闻歌算法团队研发。(Repo for YaYi Chinese LLMs based on LlaMA2 & BLOOM)

Unify Efficient Fine-Tuning of 100+ LLMs

Code and documents of LongLoRA and LongAlpaca (ICLR 2024 Oral)

OneTrainer is a one-stop solution for all your stable diffusion training needs.