v0.8.0: Poly PEFT method, LoRA improvements, Documentation improvements and more
Parameter-efficient fine-tuning (PEFT) for cross-task generalization consists of pre-training adapters on a multi-task training set before few-shot adaptation to test tasks. Polytropon [Ponti et al., 2023] (𝙿𝚘𝚕𝚢) jointly learns an inventory of adapters and a routing function that selects a (variable-size) subset of adapters for each task during both pre-training and few-shot adaptation. To put simply, you can think of it as Mixture of Expert Adapters. 𝙼𝙷𝚁 (Multi-Head Routing) combines subsets of adapter parameters and outperforms 𝙿𝚘𝚕𝚢 under a comparable parameter budget; by only fine-tuning the routing function and not the adapters (𝙼𝙷𝚁-z) they achieve competitive performance with extreme parameter efficiency.
Now, you can specify all-linear to target_modules param of LoraConfig to target all the linear layers which has shown to perform better in QLoRA paper than only targeting query and valuer attention layers
Embedding layers of base models are now automatically saved when the embedding layers are resized when fine-tuning with PEFT approaches like LoRA. This enables extending the vocabulary of tokenizer to include special tokens. This is a common use-case when doing the following:
New option use_rslora in LoraConfig. Use it for ranks greater than 32 and see the increase in fine-tuning performance (same or better performance for ranks lower than 32 as well).
all-linear flag by @SumanthRH in https://github.com/huggingface/peft/pull/1357Tests] Add bitsandbytes installed from source on new docker images by @younesbelkada in https://github.com/huggingface/peft/pull/1275bnb] Add bnb nightly workflow by @younesbelkada in https://github.com/huggingface/peft/pull/1282bnb-nightly] Address final comments by @younesbelkada in https://github.com/huggingface/peft/pull/1287prepare_inputs_for_generation logic for Prompt Learning methods by @pacman100 in https://github.com/huggingface/peft/pull/1352all-linear flag by @SumanthRH in https://github.com/huggingface/peft/pull/1357Full Changelog: https://github.com/huggingface/peft/compare/v0.7.1...v0.8.0
Fetched April 7, 2026