ToolAI Infrastructurev0.13

LoRA Library

by Hugging Face · free · Last verified 2026-03-17

The LoRA Library, integrated within Hugging Face's PEFT (Parameter-Efficient Fine-Tuning) package, provides tools to create, share, and use LoRA adapters. It allows for the efficient customization of large pre-trained models by training only a small number of new weights, drastically reducing computational costs and storage requirements compared to full fine-tuning.

https://huggingface.co/docs/peft ↗

B—Above Average

Adoption: B+Quality: AFreshness: ACitations: B+Engagement: F

Specifications

License: Apache-2.0
Pricing: free
Capabilities: Low-Rank Adaptation (LoRA) training, Adapter loading from Hugging Face Hub, Merging multiple adapters into a single model, Support for various PEFT methods (e.g., Prefix Tuning, P-Tuning), Integration with 8-bit and 4-bit quantization for further memory reduction, Dynamic adapter loading and switching, Compatibility with Transformers and Diffusers libraries, Fine-tuning specific model layers or modules
Integrations: [object Object], [object Object], [object Object], [object Object], [object Object]
Use Cases: [object Object], [object Object], [object Object], [object Object]
API Available: Yes
SDK Languages: python
Deployment: self-hosted
Rate Limits: N/A (open-source)
Data Privacy: Self-hosted, user-managed
Tags: lora, adapters, model-hub, fine-tuning, peft, parameter-efficient-fine-tuning, hugging-face, model-customization, transfer-learning, llm, diffusion-models
Added: 2026-03-17
Completeness: 0.6%

Index Score

63.1

Adoption

Quality

Freshness

Citations

Engagement

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