Latest posts tagged with #peft on Bluesky
Zapraszamy na naszego bloga - dostępny jest nowy artykuł o technikach optymalizacji dużych modeli językowych.
Opisujemy kwantyzację, pruning, destylację, PEFT oraztechniki optymalizacji inferencji, takie jak batching zapytań, KV cache i dekodowanie spekulatywne.
azurro.pl/techniki-opt...
#AI #PEFT
2025년 최신! LLM Fine-tuning 완벽 가이드. Full Fine-tuning, LoRA, QLoRA 비교부터 GPT-4o 파인튜닝 실제 비용($7.50~), 최소 데이터 개수(50~200개로 충분!), Google Colab 무료 실습 코드까지. 전이학습과의 차이, DoRA/QDoRA 최신 기법 포함!
#AI맞춤화 #DoRA #Finetuning #GoogleColab #GPT4파인튜닝 #Llama파인튜닝 #LLM미세조정 #LoRA #PEFT #QLoRA
doyouknow.kr/581/fine-tun...
TiTok Framework Boosts LoRA Transfer with Token-Level Contrast
TiTok boosts LoRA adapter transfer by 4‑8% and drops the need for any extra discriminator, using a contrastive excess between the model with and without the adapter. Read more: getnews.me/titok-framework-boosts-l... #lora #peft
DoRAN Boosts Low-Rank Fine‑Tuning via Noise and Dynamic Networks
DoRAN adds noise to DoRA’s denominator and uses networks to generate low‑rank matrices, boosting stability and data‑efficiency; Oct 5 2025 experiments show it outperforms LoRA. Read more: getnews.me/doran-boosts-low-rank-fi... #doran #peft #lowrank
Permissioned LLMs: Enforcing Access Control in Enterprise AI Models
Permissioned LLMs add a query‑level enforcement layer using PEFT adapters, LoRA and prefix‑tuning, and were tested on five benchmarks (GPQA, RCV1, SimpleQA, WMDP, PubMedQA). Read more: getnews.me/permissioned-llms-enforc... #permissionedllms #peft #ai
Activated LoRA: Faster Switching for Fine‑Tuned Language Models
Activated LoRA (aLoRA) lets developers switch fine‑tuned adapters without KV‑cache recompute; it’s available in Hugging Face’s PEFT library. The paper’s latest version came out in October 2025. Read more: getnews.me/activated-lora-faster-sw... #alora #peft
Fine-Tuning Large Language Models Boosts Secure Code Generation
Fine‑tuning LLMs with PEFT raised secure‑code scores by up to 6.4% for C and 5.0% for C++ in a September 2025 study; LoRA showed the biggest gains on function‑level data. getnews.me/fine-tuning-large-langua... #peft #lora
Efficient Orthogonal Fine‑Tuning via Principal Subspace Adaptation
Researchers released PSOFT, a method that limits orthogonal fine‑tuning to a model’s principal subspace, cutting parameters and memory while matching PEFT performance across 35 NLP and vision tasks. getnews.me/efficient-orthogonal-fin... #psoft #peft
WeatherPEFT: Efficient Fine‑Tuning for Weather Foundation Models
WeatherPEFT lets large weather models match full‑model tuning accuracy while training with only a fraction of parameters, using Task‑Adaptive Dynamic Prompting and Fisher‑guided selection. Read more: getnews.me/weatherpeft-efficient-fi... #weatherai #peft
Blockwise Hadamard Adaptation Boosts Efficient LLM Fine‑Tuning
Blockwise Hadamard high‑Rank Adaptation (BHRA) improves PEFT, beating baselines on eight commonsense and two arithmetic tasks with Llama‑3.2 (1 B/3 B), Mistral‑7 B and Gemma‑2 (9 B). getnews.me/blockwise-hadamard-adapt... #bhra #peft #llm
LoSiA Introduces Efficient High‑Rank Fine‑Tuning for AI Models
LoSiA offers a high‑rank PEFT that trains only a critical sub‑network; its LoSiA‑Pro variant cuts training latency by ~27% versus LoRA and will be presented at EMNLP 2025. getnews.me/losia-introduces-efficie... #losia #peft
Localized LoRA: Structured Low‑Rank Updates for Efficient Fine‑Tuning
Localized LoRA partitions a model’s weight matrix into structured blocks, giving each its own low‑rank update while keeping the total trainable parameters unchanged. Read more: getnews.me/localized-lora-structure... #localizedlora #peft #lowrank
Rehearsal-Free Continual Learning with Pretrained Models: A Review
A new review shows lightweight PEFT baselines match performance of rehearsal‑free continual learning methods, and query mechanisms add no benefit. Parameter budget drives gains. getnews.me/rehearsal-free-continual... #peft #continuallearning
Bias-Efficient Fine-Tuning Boosts Language Model Performance
BEFT fine‑tunes only bias terms in transformers, handling models from ~100 M to several B parameters, and matches or exceeds heavier PEFT methods in low‑resource tests. Read more: getnews.me/bias-efficient-fine-tuni... #biasefficient #peft #llm
Data- and Parameter-Efficient Techniques Boost Arabic Dialect ID
Researchers found that LoRA‑based fine‑tuning outperforms soft‑prompted encoders, which in turn beat hard‑prompted large language models for Arabic Dialect Identification. Read more: getnews.me/data-and-parameter-effic... #arabicdialect #peft #lora
Activation Function Tuning Boosts Efficient Fine‑Tuning in AI Models
NoRA updates only 0.4% of parameters (≈0.02 M) and lifts CIFAR‑10 accuracy by 0.17%; on LLaMA‑3‑8B tuning, MMLU improves up to 0.8%. This low‑rank update adds minimal compute cost. getnews.me/activation-function-tuni... #activationfunction #peft
Activation‑Space Tuning Improves Parameter‑Efficient Fine‑Tuning
Activation‑space tuning (NoRA) updates only 0.4% of a vision transformer’s parameters (~0.02 M) and yields +0.17% accuracy on CIFAR‑10 and +0.27% on CIFAR‑100. Read more: getnews.me/activation-space-tuning-... #activationtuning #peft #visiontransformer
Hierarchical Adapter Merging Boosts Scalable Continual Learning
Hierarchical Adapter Merging (HAM) was tested on three vision benchmarks and consistently outperformed state‑of‑the‑art PEFT methods, especially as the number of tasks increased. Read more: getnews.me/hierarchical-adapter-mer... #continuallearning #peft
Parameter-Efficient Fine-Tuning Improves Security of Code‑Generating LLMs
Prompt‑tuning on CodeGen2 16B lifted the Overall‑Secure‑Rate to 80.86%; raising the temperature boosted security to 87.65%. Read more: getnews.me/parameter-efficient-fine... #prompttuning #peft
HEFT: Hierarchical fine-tuning boosts LLM reasoning efficiency
HEFT combines LoRA and ReFT for hierarchical fine‑tuning, achieving 85.17% accuracy on BoolQ with just three epochs, beating LoRA‑only after twenty epochs. Read more: getnews.me/heft-hierarchical-fine-t... #heft #peft #llm
Want to fine-tune LLMs without a #GPU cluster? Join our live online training “Fine-tuning on one GPU” for anyone building smart AI w/ lean resources.
8 September 2025 | 09:00–12:30 CET
events.asc.ac.at/event/203/
#LLM #LoRA #PEFT #AItraining #Quantisation #AIonABudget #HuggingFace #Python
От понимания файнтюнинга LLM до файнтюнинга мультимодальных моделей Что такое дообучение LLM и зачем оно нужн...
#дообучение #LLM #PEFT #методы #LoRA #QLoRA #AdaLoRA #P-Tuning #BitFit
Origin | Interest | Match
Эффективный инференс множества LoRA адаптеров LoRA — популярный метод дообучения больших моделей на небольши...
#multilora #offline #inference #async #inference #vllm #TensorRT-LLM #tensorrt #peft #inference #benchmark
Origin | Interest | Match
Train LLMs to Talk Like You on Social Media, Using Consumer Hardware Use your own comments on soc...
medium.com/data-science-collective/...
#hugging-face #llm #peft #ai […]
Missed out on #Swift tickets? No worries—swing by our #SVFT poster at #NeurIPS2024 and catch *real* headliners! 🎤💃🕺
📌Where: East Exhibit Hall A-C #2207, Poster Session 4 East
⏲️When: Thu 12 Dec, 4:30 PM - 7:30 PM PST
#AI #MachineLearning #PEFT #NeurIPS24
