HuggingFace PEFT
by HuggingFace · Open-source and free. · Last verified 2026-03-26T17:38:01.816Z
A Python library for Parameter-Efficient Fine-Tuning (PEFT) methods. It enables efficient adaptation of large pre-trained models to downstream tasks with minimal computational cost and memory footprint by only updating a small subset of model parameters.
https://huggingface.co/docs/peft/index ↗F
F—Critical
Adoption: FQuality: FFreshness: A+Citations: FEngagement: F
Specifications
- Pricing
- Open-source and free.
- Capabilities
- Implements LoRA, Prefix Tuning, P-tuning, Prompt Tuning, Significantly reduces memory footprint for fine-tuning, Accelerates training time for large models, Compatible with HuggingFace Transformers and Diffusers, Enables fine-tuning on consumer-grade GPUs
- Integrations
- HuggingFace Transformers, PyTorch, TensorFlow, JAX
- Use Cases
- Fine-tuning large language models with limited GPU resources, Adapting foundation models to specific tasks quickly and cost-effectively, Reducing training costs for custom models, Experimenting with different fine-tuning strategies for LLMs
- API Available
- Yes
- Tags
- fine-tuning, parameter-efficient, LLM optimization, model adaptation, low-resource training, deep learning
- Added
- 2026-03-26T17:38:01.816Z
- Completeness
- 0.6%
Index Score
0Adoption
0
Quality
0
Freshness
100
Citations
0
Engagement
0
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