{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/scaling-down-to-scale-up-a-guide-to-parameter","title":"Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning","arxiv_id":"2303.15647","date":"2023-03-28","proceeding":null,"authors":["Vladislav Lialin","Vijeta Deshpande","Xiaowei Yao","Anna Rumshisky"],"abstract":"This paper presents a systematic overview of parameter-efficient fine-tuning methods, covering over 50 papers published between early 2019 and mid-2024. These methods aim to address the challenges of fine-tuning large language models by training only a small subset of parameters. We provide a taxonomy that covers a broad range of methods and present a detailed method comparison with a specific focus on real-life efficiency in fine-tuning multibillion-scale language models. We also conduct an extensive head-to-head experimental comparison of 15 diverse PEFT methods, evaluating their performance and efficiency on models up to 11B parameters. Our findings reveal that methods previously shown to surpass a strong LoRA baseline face difficulties in resource-constrained settings, where hyperparameter optimization is limited and the network is fine-tuned only for a few epochs. Finally, we provide a set of practical recommendations for using PEFT methods and outline potential future research directions.","url_abs":"https://arxiv.org/abs/2303.15647v2","url_pdf":"https://arxiv.org/pdf/2303.15647v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"scaling-down-to-scale-up-a-guide-to-parameter","repo_url":"https://github.com/guitaricet/peft_comparison","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"scaling-down-to-scale-up-a-guide-to-parameter","repo_url":"https://github.com/leiluk1/codesearcher","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"hyperparameter-optimization","task_name":"Hyperparameter Optimization"},{"task_slug":"parameter-efficient-fine-tuning","task_name":"parameter-efficient fine-tuning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2303.15647","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.15647"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/guitaricet/peft_comparison","reach":{"status":"ok","spdx":"Apache-2.0"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/leiluk1/codesearcher","reach":{"status":"ok"}}],"summary":{"unverified":6},"by_repo_kind":{"official":{"samples":6,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"1c18de6554e2fdf6","entry":"adjust_tensors_for_parallel","repo":"guitaricet/peft_comparison","repo_kind":"official","path":"adapter-transformers/src/adapters/composition.py","file_url":"https://github.com/guitaricet/peft_comparison/blob/HEAD/adapter-transformers/src/adapters/composition.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"1c18de6554e2fdf6"}},{"code_sha256_prefix":"0f377af72b3e204e","entry":"get_head_config_and_rename_list","repo":"guitaricet/peft_comparison","repo_kind":"official","path":"adapter-transformers/src/adapters/head_utils.py","file_url":"https://github.com/guitaricet/peft_comparison/blob/HEAD/adapter-transformers/src/adapters/head_utils.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"0f377af72b3e204e"}},{"code_sha256_prefix":"206d94a12134c9c2","entry":"parse_composition","repo":"guitaricet/peft_comparison","repo_kind":"official","path":"adapter-transformers/src/adapters/composition.py","file_url":"https://github.com/guitaricet/peft_comparison/blob/HEAD/adapter-transformers/src/adapters/composition.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"206d94a12134c9c2"}},{"code_sha256_prefix":"bf63c932637bbcb5","entry":"parse_config_string","repo":"guitaricet/peft_comparison","repo_kind":"official","path":"peft_comparison/utils.py","file_url":"https://github.com/guitaricet/peft_comparison/blob/HEAD/peft_comparison/utils.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"bf63c932637bbcb5"}},{"code_sha256_prefix":"66972b47262ebdc3","entry":"parse_heads_from_composition","repo":"guitaricet/peft_comparison","repo_kind":"official","path":"adapter-transformers/src/adapters/composition.py","file_url":"https://github.com/guitaricet/peft_comparison/blob/HEAD/adapter-transformers/src/adapters/composition.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"66972b47262ebdc3"}},{"code_sha256_prefix":"00ec6b1d254c92ae","entry":"postprocess_summarization","repo":"guitaricet/peft_comparison","repo_kind":"official","path":"peft_comparison/text2text_utils.py","file_url":"https://github.com/guitaricet/peft_comparison/blob/HEAD/peft_comparison/text2text_utils.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"00ec6b1d254c92ae"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}