{"adoption": {"forks": 115, "observed_at": "2026-08-28T04:04:04.598691+00:00", "stars": 1233}, "canonical_url": "https://ross.abutalabs.com/products/llm-adapters", "card": {"archived": false, "artifact_type": "library", "description": "Code for our EMNLP 2023 Paper: \"LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models\"", "domain": ["large-language-models", "machine-learning", "deep-learning"], "enriched": true, "function": ["llm-training", "machine-learning", "sdk"], "health_score": 20, "homepage": "https://arxiv.org/abs/2304.01933", "language": "Python", "license": "Apache-2.0", "license_family": "permissive", "maturity": "maintenance", "member_repos": ["AGI-Edgerunners/LLM-Adapters"], "name": "AGI-Edgerunners/LLM-Adapters", "platform": ["python"], "pushed_at": "2024-03-10T08:20:15+00:00", "repo": "AGI-Edgerunners/LLM-Adapters", "stars": 1233, "tags": ["peft", "lora", "adapters", "fine-tuning", "prompt-tuning", "huggingface", "research-code", "llama", "natural-language-processing", "gpu", "linux"], "topics": ["adapters", "fine-tuning", "large-language-models", "parameter-efficient"], "urls": [], "use_cases": ["fine-tune llama with lora adapters", "parameter-efficient fine-tuning of large language models", "compare adapter types like bottleneck vs parallel adapters on llms", "reproduce emnlp 2023 llm-adapters paper experiments", "train adapters on commonsense170k dataset", "apply prefix tuning or p-tuning to open-access llms"], "what_it_is": "LLM-Adapters is a Python framework extending HuggingFace's PEFT library that integrates various adapter types (LoRA, series/parallel adapters, prefix/prompt tuning) into open-access LLMs like LLaMA, BLOOM, and GPT-J for parameter-efficient fine-tuning. It accompanies an EMNLP 2023 paper and includes benchmark datasets such as math10k and commonsense170k.", "when_to_avoid": ["you need actively maintained tooling with support for the latest LLMs - the repo has seen limited updates since 2024", "you want full fine-tuning rather than parameter-efficient methods", "you need production-grade training infrastructure rather than research code"], "when_to_choose": ["you want a unified framework to experiment with multiple PEFT adapter methods on LLaMA, BLOOM, GPT-J, or OPT", "you need the paper's benchmark datasets and adapter checkpoints for research reproduction", "you want to study adapter placement and hyperparameter effects on fine-tuning performance"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/llm-adapters", "repo": "AGI-Edgerunners/LLM-Adapters", "role": "main", "score": 30}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:04:04.598691+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T08:22:12.680865+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "854425ad888d96cf2a3222c1b4e196c4a11db861456c5a682d721a27d6b42d24", "fetched_at": "2026-08-28T04:04:04.598691+00:00", "kind": "readme", "missing": false, "url": "https://github.com/AGI-Edgerunners/LLM-Adapters"}, {"content_hash": "90cdcbf30a0327a3dae5d306684d5957e015273b89d4ce51abddf250b59f150b", "fetched_at": "2026-08-29T12:22:01.962058+00:00", "kind": "homepage", "missing": false, "url": "https://arxiv.org/abs/2304.01933"}, {"content_hash": "cca9c3a11c56b1212864e03fb8a5511a3bdb6df53398ba4dd2ed778f931607dd", "fetched_at": "2026-08-29T12:22:01.971349+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/donate.html"}, {"content_hash": "47cbc55ff1deaca3f36b463373de863a7053d91cacf9f95725618e11610209ae", "fetched_at": "2026-08-29T12:22:01.975397+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/ourmembers.html"}, {"content_hash": "a1f16f915a9ad89ee57c3e929a1b6577d481f52c05f8015fc720b16ee8014f19", "fetched_at": "2026-08-29T12:22:01.977519+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about"}, {"content_hash": "b14a8d05a0ec337409ab63bffd91306b5317b16fac358aa6d1fe6afbaf3c8628", "fetched_at": "2026-08-29T12:22:01.973196+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/labs/index.html"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:04:04.598691+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T08:22:12.680865+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "854425ad888d96cf2a3222c1b4e196c4a11db861456c5a682d721a27d6b42d24", "fetched_at": "2026-08-28T04:04:04.598691+00:00", "kind": "readme", "missing": false, "url": "https://github.com/AGI-Edgerunners/LLM-Adapters"}, {"content_hash": "90cdcbf30a0327a3dae5d306684d5957e015273b89d4ce51abddf250b59f150b", "fetched_at": "2026-08-29T12:22:01.962058+00:00", "kind": "homepage", "missing": false, "url": "https://arxiv.org/abs/2304.01933"}, {"content_hash": "cca9c3a11c56b1212864e03fb8a5511a3bdb6df53398ba4dd2ed778f931607dd", "fetched_at": "2026-08-29T12:22:01.971349+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/donate.html"}, {"content_hash": "47cbc55ff1deaca3f36b463373de863a7053d91cacf9f95725618e11610209ae", "fetched_at": "2026-08-29T12:22:01.975397+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/ourmembers.html"}, {"content_hash": "a1f16f915a9ad89ee57c3e929a1b6577d481f52c05f8015fc720b16ee8014f19", "fetched_at": "2026-08-29T12:22:01.977519+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about"}, {"content_hash": "b14a8d05a0ec337409ab63bffd91306b5317b16fac358aa6d1fe6afbaf3c8628", "fetched_at": "2026-08-29T12:22:01.973196+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/labs/index.html"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T08:22:12.680865+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "854425ad888d96cf2a3222c1b4e196c4a11db861456c5a682d721a27d6b42d24", "fetched_at": "2026-08-28T04:04:04.598691+00:00", "kind": "readme", "missing": false, "url": "https://github.com/AGI-Edgerunners/LLM-Adapters"}, {"content_hash": "90cdcbf30a0327a3dae5d306684d5957e015273b89d4ce51abddf250b59f150b", "fetched_at": "2026-08-29T12:22:01.962058+00:00", "kind": "homepage", "missing": false, "url": "https://arxiv.org/abs/2304.01933"}, {"content_hash": "cca9c3a11c56b1212864e03fb8a5511a3bdb6df53398ba4dd2ed778f931607dd", "fetched_at": "2026-08-29T12:22:01.971349+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/donate.html"}, {"content_hash": "47cbc55ff1deaca3f36b463373de863a7053d91cacf9f95725618e11610209ae", "fetched_at": "2026-08-29T12:22:01.975397+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/ourmembers.html"}, {"content_hash": "a1f16f915a9ad89ee57c3e929a1b6577d481f52c05f8015fc720b16ee8014f19", "fetched_at": "2026-08-29T12:22:01.977519+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about"}, {"content_hash": "b14a8d05a0ec337409ab63bffd91306b5317b16fac358aa6d1fe6afbaf3c8628", "fetched_at": "2026-08-29T12:22:01.973196+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/labs/index.html"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:04:04.598691+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:04:04.598691+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:04:04.598691+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T08:22:12.680865+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "854425ad888d96cf2a3222c1b4e196c4a11db861456c5a682d721a27d6b42d24", "fetched_at": "2026-08-28T04:04:04.598691+00:00", "kind": "readme", "missing": false, "url": "https://github.com/AGI-Edgerunners/LLM-Adapters"}, {"content_hash": "90cdcbf30a0327a3dae5d306684d5957e015273b89d4ce51abddf250b59f150b", "fetched_at": "2026-08-29T12:22:01.962058+00:00", "kind": "homepage", "missing": false, "url": "https://arxiv.org/abs/2304.01933"}, {"content_hash": "cca9c3a11c56b1212864e03fb8a5511a3bdb6df53398ba4dd2ed778f931607dd", "fetched_at": "2026-08-29T12:22:01.971349+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/donate.html"}, {"content_hash": "47cbc55ff1deaca3f36b463373de863a7053d91cacf9f95725618e11610209ae", "fetched_at": "2026-08-29T12:22:01.975397+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/ourmembers.html"}, {"content_hash": "a1f16f915a9ad89ee57c3e929a1b6577d481f52c05f8015fc720b16ee8014f19", "fetched_at": "2026-08-29T12:22:01.977519+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about"}, {"content_hash": "b14a8d05a0ec337409ab63bffd91306b5317b16fac358aa6d1fe6afbaf3c8628", "fetched_at": "2026-08-29T12:22:01.973196+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/labs/index.html"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:04:04.598691+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:04:04.598691+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T08:22:12.680865+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "854425ad888d96cf2a3222c1b4e196c4a11db861456c5a682d721a27d6b42d24", "fetched_at": "2026-08-28T04:04:04.598691+00:00", "kind": "readme", "missing": false, "url": "https://github.com/AGI-Edgerunners/LLM-Adapters"}, {"content_hash": "90cdcbf30a0327a3dae5d306684d5957e015273b89d4ce51abddf250b59f150b", "fetched_at": "2026-08-29T12:22:01.962058+00:00", "kind": "homepage", "missing": false, "url": "https://arxiv.org/abs/2304.01933"}, {"content_hash": "cca9c3a11c56b1212864e03fb8a5511a3bdb6df53398ba4dd2ed778f931607dd", "fetched_at": "2026-08-29T12:22:01.971349+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/donate.html"}, {"content_hash": "47cbc55ff1deaca3f36b463373de863a7053d91cacf9f95725618e11610209ae", "fetched_at": "2026-08-29T12:22:01.975397+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/ourmembers.html"}, {"content_hash": "a1f16f915a9ad89ee57c3e929a1b6577d481f52c05f8015fc720b16ee8014f19", "fetched_at": "2026-08-29T12:22:01.977519+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about"}, {"content_hash": "b14a8d05a0ec337409ab63bffd91306b5317b16fac358aa6d1fe6afbaf3c8628", "fetched_at": "2026-08-29T12:22:01.973196+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/labs/index.html"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:04:04.598691+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:04:04.598691+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:04:04.598691+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T08:22:12.680865+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "854425ad888d96cf2a3222c1b4e196c4a11db861456c5a682d721a27d6b42d24", "fetched_at": "2026-08-28T04:04:04.598691+00:00", "kind": "readme", "missing": false, "url": "https://github.com/AGI-Edgerunners/LLM-Adapters"}, {"content_hash": "90cdcbf30a0327a3dae5d306684d5957e015273b89d4ce51abddf250b59f150b", "fetched_at": "2026-08-29T12:22:01.962058+00:00", "kind": "homepage", "missing": false, "url": "https://arxiv.org/abs/2304.01933"}, {"content_hash": "cca9c3a11c56b1212864e03fb8a5511a3bdb6df53398ba4dd2ed778f931607dd", "fetched_at": "2026-08-29T12:22:01.971349+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/donate.html"}, {"content_hash": "47cbc55ff1deaca3f36b463373de863a7053d91cacf9f95725618e11610209ae", "fetched_at": "2026-08-29T12:22:01.975397+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/ourmembers.html"}, {"content_hash": "a1f16f915a9ad89ee57c3e929a1b6577d481f52c05f8015fc720b16ee8014f19", "fetched_at": "2026-08-29T12:22:01.977519+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about"}, {"content_hash": "b14a8d05a0ec337409ab63bffd91306b5317b16fac358aa6d1fe6afbaf3c8628", "fetched_at": "2026-08-29T12:22:01.973196+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/labs/index.html"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:04:04.598691+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:04:04.598691+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T08:22:12.680865+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "854425ad888d96cf2a3222c1b4e196c4a11db861456c5a682d721a27d6b42d24", "fetched_at": "2026-08-28T04:04:04.598691+00:00", "kind": "readme", "missing": false, "url": "https://github.com/AGI-Edgerunners/LLM-Adapters"}, {"content_hash": "90cdcbf30a0327a3dae5d306684d5957e015273b89d4ce51abddf250b59f150b", "fetched_at": "2026-08-29T12:22:01.962058+00:00", "kind": "homepage", "missing": false, "url": "https://arxiv.org/abs/2304.01933"}, {"content_hash": "cca9c3a11c56b1212864e03fb8a5511a3bdb6df53398ba4dd2ed778f931607dd", "fetched_at": "2026-08-29T12:22:01.971349+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/donate.html"}, {"content_hash": "47cbc55ff1deaca3f36b463373de863a7053d91cacf9f95725618e11610209ae", "fetched_at": "2026-08-29T12:22:01.975397+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/ourmembers.html"}, {"content_hash": "a1f16f915a9ad89ee57c3e929a1b6577d481f52c05f8015fc720b16ee8014f19", "fetched_at": "2026-08-29T12:22:01.977519+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about"}, {"content_hash": "b14a8d05a0ec337409ab63bffd91306b5317b16fac358aa6d1fe6afbaf3c8628", "fetched_at": "2026-08-29T12:22:01.973196+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/labs/index.html"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T08:22:12.680865+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "854425ad888d96cf2a3222c1b4e196c4a11db861456c5a682d721a27d6b42d24", "fetched_at": "2026-08-28T04:04:04.598691+00:00", "kind": "readme", "missing": false, "url": "https://github.com/AGI-Edgerunners/LLM-Adapters"}, {"content_hash": "90cdcbf30a0327a3dae5d306684d5957e015273b89d4ce51abddf250b59f150b", "fetched_at": "2026-08-29T12:22:01.962058+00:00", "kind": "homepage", "missing": false, "url": "https://arxiv.org/abs/2304.01933"}, {"content_hash": "cca9c3a11c56b1212864e03fb8a5511a3bdb6df53398ba4dd2ed778f931607dd", "fetched_at": "2026-08-29T12:22:01.971349+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/donate.html"}, {"content_hash": "47cbc55ff1deaca3f36b463373de863a7053d91cacf9f95725618e11610209ae", "fetched_at": "2026-08-29T12:22:01.975397+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/ourmembers.html"}, {"content_hash": "a1f16f915a9ad89ee57c3e929a1b6577d481f52c05f8015fc720b16ee8014f19", "fetched_at": "2026-08-29T12:22:01.977519+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about"}, {"content_hash": "b14a8d05a0ec337409ab63bffd91306b5317b16fac358aa6d1fe6afbaf3c8628", "fetched_at": "2026-08-29T12:22:01.973196+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/labs/index.html"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T08:22:12.680865+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "854425ad888d96cf2a3222c1b4e196c4a11db861456c5a682d721a27d6b42d24", "fetched_at": "2026-08-28T04:04:04.598691+00:00", "kind": "readme", "missing": false, "url": "https://github.com/AGI-Edgerunners/LLM-Adapters"}, {"content_hash": "90cdcbf30a0327a3dae5d306684d5957e015273b89d4ce51abddf250b59f150b", "fetched_at": "2026-08-29T12:22:01.962058+00:00", "kind": "homepage", "missing": false, "url": "https://arxiv.org/abs/2304.01933"}, {"content_hash": "cca9c3a11c56b1212864e03fb8a5511a3bdb6df53398ba4dd2ed778f931607dd", "fetched_at": "2026-08-29T12:22:01.971349+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/donate.html"}, {"content_hash": "47cbc55ff1deaca3f36b463373de863a7053d91cacf9f95725618e11610209ae", "fetched_at": "2026-08-29T12:22:01.975397+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/ourmembers.html"}, {"content_hash": "a1f16f915a9ad89ee57c3e929a1b6577d481f52c05f8015fc720b16ee8014f19", "fetched_at": "2026-08-29T12:22:01.977519+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about"}, {"content_hash": "b14a8d05a0ec337409ab63bffd91306b5317b16fac358aa6d1fe6afbaf3c8628", "fetched_at": "2026-08-29T12:22:01.973196+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/labs/index.html"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T08:22:12.680865+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "854425ad888d96cf2a3222c1b4e196c4a11db861456c5a682d721a27d6b42d24", "fetched_at": "2026-08-28T04:04:04.598691+00:00", "kind": "readme", "missing": false, "url": "https://github.com/AGI-Edgerunners/LLM-Adapters"}, {"content_hash": "90cdcbf30a0327a3dae5d306684d5957e015273b89d4ce51abddf250b59f150b", "fetched_at": "2026-08-29T12:22:01.962058+00:00", "kind": "homepage", "missing": false, "url": "https://arxiv.org/abs/2304.01933"}, {"content_hash": "cca9c3a11c56b1212864e03fb8a5511a3bdb6df53398ba4dd2ed778f931607dd", "fetched_at": "2026-08-29T12:22:01.971349+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/donate.html"}, {"content_hash": "47cbc55ff1deaca3f36b463373de863a7053d91cacf9f95725618e11610209ae", "fetched_at": "2026-08-29T12:22:01.975397+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about/ourmembers.html"}, {"content_hash": "a1f16f915a9ad89ee57c3e929a1b6577d481f52c05f8015fc720b16ee8014f19", "fetched_at": "2026-08-29T12:22:01.977519+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/about"}, {"content_hash": "b14a8d05a0ec337409ab63bffd91306b5317b16fac358aa6d1fe6afbaf3c8628", "fetched_at": "2026-08-29T12:22:01.973196+00:00", "kind": "site_page", "missing": false, "url": "https://info.arxiv.org/labs/index.html"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 0, "longevity": 89, "rhythm": 35}, "computed_at": "2026-09-02T17:46:02.011165+00:00", "flags": ["no_releases"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 1253, "days_push": 906, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 30, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}