Awesome Data Analysis
Section: Tools · Library for efficiently adapting large pretrained models.
FreshScore 80
Entry
PEFT
Appears in 7 awesome lists
Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of pre-trained language models (PLMs) to various downstream applications without fine-tuning all the model's parameters.
Open github.comhuggingface/peft
Found in these lists
Awesome LLMOps
Section: Foundation Model Fine Tuning · State-of-the-art Parameter-Efficient Fine-Tuning.
ActiveScore 75
awesome-nlp
Section: Efficient and Small Language Models · HuggingFace library bundling LoRA, prefix tuning, IA3, and others.
FreshScore 90
Awesome Open Source AI
Section: 7. Training & Fine-tuning Ecosystem · Official library with LoRA, QLoRA, DoRA, etc.
FreshScore 89
Awesome Production Machine Learning
Section: Computation and Communication Optimisation · Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of pre-trained language models (PLMs) to various downstream applications without fine-tuning all the model's parameters.
FreshScore 92
Awesome Python
Section: AI and Agents · A library for parameter-efficient fine-tuning of large pretrained models.
FreshScore 94
awesome-python
Section: LLM and Inference · 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
FreshScore 81
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