{"adoption": {"forks": 89, "observed_at": "2026-08-28T04:03:51.796210+00:00", "stars": 1173}, "canonical_url": "https://ross.abutalabs.com/products/mezo", "card": {"archived": false, "artifact_type": "library", "description": "[NeurIPS 2023] MeZO: Fine-Tuning Language Models with Just Forward Passes. https://arxiv.org/abs/2305.17333", "domain": ["large-language-models", "machine-learning", "deep-learning"], "enriched": true, "function": ["llm-training", "machine-learning", "deep-learning"], "health_score": 20, "homepage": null, "language": "Python", "license": "MIT", "license_family": "permissive", "maturity": "stable", "member_repos": ["princeton-nlp/MeZO"], "name": "princeton-nlp/MeZO", "platform": ["python"], "pushed_at": "2024-01-11T18:07:52+00:00", "repo": "princeton-nlp/MeZO", "stars": 1173, "tags": ["zeroth-order-optimization", "memory-efficient", "fine-tuning", "lora", "prefix-tuning", "research-code", "huggingface-trainer", "gpu"], "topics": [], "urls": [], "use_cases": ["fine-tune a 30B parameter language model on a single 80GB GPU", "train LLMs without backpropagation to reduce GPU memory usage", "optimize non-differentiable objectives like accuracy or F1", "apply LoRA or prefix tuning with zeroth-order optimization", "reproduce NeurIPS 2023 MeZO paper experiments on OPT and RoBERTa models"], "what_it_is": "MeZO is a memory-efficient zeroth-order optimizer that fine-tunes language models using only forward passes, with the same memory footprint as inference. It is a research implementation based on HuggingFace's Trainer, supporting full-parameter and parameter-efficient tuning like LoRA and prefix tuning.", "when_to_avoid": ["you need fast convergence on small models where Adam fine-tuning fits in memory", "you require a production-ready training framework rather than research code", "your task benefits strongly from gradient-based optimization"], "when_to_choose": ["GPU memory is the bottleneck for fine-tuning large language models", "you need to optimize non-differentiable objectives", "you want parameter-efficient fine-tuning without storing optimizer states"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/mezo", "repo": "princeton-nlp/MeZO", "role": "main", "score": 29}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:03:51.796210+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T06:28:24.481825+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "830188ac5c8cc6e8ffcf4aa3eda9fe79202405e5935cd63baba30fa230b39507", "fetched_at": "2026-08-28T04:03:51.796210+00:00", "kind": "readme", "missing": false, "url": "https://github.com/princeton-nlp/MeZO"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:03:51.796210+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T06:28:24.481825+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "830188ac5c8cc6e8ffcf4aa3eda9fe79202405e5935cd63baba30fa230b39507", "fetched_at": "2026-08-28T04:03:51.796210+00:00", "kind": "readme", "missing": false, "url": "https://github.com/princeton-nlp/MeZO"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T06:28:24.481825+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "830188ac5c8cc6e8ffcf4aa3eda9fe79202405e5935cd63baba30fa230b39507", "fetched_at": "2026-08-28T04:03:51.796210+00:00", "kind": "readme", "missing": false, "url": "https://github.com/princeton-nlp/MeZO"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:03:51.796210+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:03:51.796210+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:03:51.796210+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T06:28:24.481825+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "830188ac5c8cc6e8ffcf4aa3eda9fe79202405e5935cd63baba30fa230b39507", "fetched_at": "2026-08-28T04:03:51.796210+00:00", "kind": "readme", "missing": false, "url": "https://github.com/princeton-nlp/MeZO"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:03:51.796210+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:03:51.796210+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T06:28:24.481825+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "830188ac5c8cc6e8ffcf4aa3eda9fe79202405e5935cd63baba30fa230b39507", "fetched_at": "2026-08-28T04:03:51.796210+00:00", "kind": "readme", "missing": false, "url": "https://github.com/princeton-nlp/MeZO"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:03:51.796210+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:03:51.796210+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:03:51.796210+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T06:28:24.481825+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "830188ac5c8cc6e8ffcf4aa3eda9fe79202405e5935cd63baba30fa230b39507", "fetched_at": "2026-08-28T04:03:51.796210+00:00", "kind": "readme", "missing": false, "url": "https://github.com/princeton-nlp/MeZO"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:03:51.796210+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:03:51.796210+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T06:28:24.481825+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "830188ac5c8cc6e8ffcf4aa3eda9fe79202405e5935cd63baba30fa230b39507", "fetched_at": "2026-08-28T04:03:51.796210+00:00", "kind": "readme", "missing": false, "url": "https://github.com/princeton-nlp/MeZO"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T06:28:24.481825+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "830188ac5c8cc6e8ffcf4aa3eda9fe79202405e5935cd63baba30fa230b39507", "fetched_at": "2026-08-28T04:03:51.796210+00:00", "kind": "readme", "missing": false, "url": "https://github.com/princeton-nlp/MeZO"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T06:28:24.481825+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "830188ac5c8cc6e8ffcf4aa3eda9fe79202405e5935cd63baba30fa230b39507", "fetched_at": "2026-08-28T04:03:51.796210+00:00", "kind": "readme", "missing": false, "url": "https://github.com/princeton-nlp/MeZO"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T06:28:24.481825+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "830188ac5c8cc6e8ffcf4aa3eda9fe79202405e5935cd63baba30fa230b39507", "fetched_at": "2026-08-28T04:03:51.796210+00:00", "kind": "readme", "missing": false, "url": "https://github.com/princeton-nlp/MeZO"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 0, "longevity": 85, "rhythm": 35}, "computed_at": "2026-09-03T02:20:16.233290+00:00", "flags": ["no_releases"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 1199, "days_push": 965, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 29, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}