Skip to main content
Angestrom home
SearchPapersModelsLive AIIntelligence
Search⌕⌘K
EnterprisePricingSign in

Stay Ahead in the AI Revolution

Weekly digest — EPI pulse, top intelligence, fresh lineage. Free, no account.

Follow Angestrom
Global source network
Synced every 5 minutes

Continuous sync from primary AI sources — indexed, enriched, and queryable in real time.

arXivHugging FaceGitHubOpenAIAnthropicDeepMindReutersBBC TechHacker NewsReddit MLVerified feedsFunding
ANGESTROM

The Intelligence Layer of Humanity. Everything AI. All in One Place.

Angestrom connects every piece of the AI ecosystem — data, models, research, companies, tools, and people.

info@angestrom.comwww.angestrom.comLucknow, Uttar Pradesh, India

Product

  • AI Search
  • AI Models
  • Research Papers
  • Companies
  • News & Events
  • GitHub Explorer
  • APIs & Tools
  • Datasets
  • Benchmarks
  • Model lifecycle
  • Funding graph
  • Contributors
  • AI Agents

Resources

  • Weekly digest
  • Documentation
  • Tutorials
  • Guides
  • News
  • Help / Start
  • Community

Company

  • About
  • Contact
  • Privacy Policy
  • Terms of Service
  • Acceptable Use

Enterprise

  • Pricing
  • Workspace
  • Contact Sales

Developer

  • Developer Hub
  • API docs
  • GitHub

Learn

  • Learning Academy
  • Roadmaps
  • Glossary
  • AI for Beginners

Popular Topics

Loading topics…
View All Topics →
© 2026 Angestrom Intelligence Private Limited. All rights reserved.
English
Theme
Angestrom home
SearchPapersModelsLive AIIntelligence
Search⌕⌘K
EnterprisePricingSign in
  1. Home
  2. /Repositories
  3. /huggingface/peft
Read original ↗
repoGitHubTrust 82 · PrimaryPublished 4d agoLive · 4d ago

huggingface/peft

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

Lineage graph

Paper → model → repo connections mined from source citations (Tier-1 exact match).

Covers

newsBeyond LoRA: Can you beat the most popular fine-tuning technique?newsHugging Face Models on Foundry Managed ComputenewsDynaMiCS: Fine-Tuning LLMs with Performance Constraints Using Dynamic Mixtures - Apple Machine Learning Research

Related across the graph

newsHugging Face Models on Foundry Managed ComputenewsDynaMiCS: Fine-Tuning LLMs with Performance Constraints Using Dynamic Mixtures - Apple Machine Learning ResearchnewsBeyond LoRA: Can you beat the most popular fine-tuning technique?
Knowledge path·NHugging Face Models on Foundry Managed Compute→NDynaMiCS: Fine-Tuning LLMs with Performance Constraints Using Dynamic Mixtures - Apple Machine Learning Research→NBeyond LoRA: Can you beat the most popular fine-tuning technique?→Rhuggingface/peft

Topics

adapterdiffusionfine-tuningllmloraparameter-efficient-learningpeftpythonpytorchtransformers

Explore

Search similar →Knowledge graph →All repos →Full intelligence feed →
Graph trust82Primary
Graph score21369