{"adoption": {"forks": 517, "observed_at": "2026-08-28T04:09:32.592859+00:00", "stars": 5942}, "canonical_url": "https://ross.abutalabs.com/products/x-transformers", "card": {"archived": false, "artifact_type": "library", "description": "A concise but complete full-attention transformer with a set of promising experimental features from various papers", "domain": ["deep-learning", "large-language-models", "artificial-intelligence"], "enriched": true, "function": ["machine-learning", "deep-learning", "llm-training"], "health_score": 97, "homepage": null, "language": "Python", "license": "MIT", "license_family": "permissive", "maturity": "active", "member_repos": ["lucidrains/x-transformers"], "name": "lucidrains/x-transformers", "platform": ["python"], "pushed_at": "2026-08-26T19:18:13+00:00", "repo": "lucidrains/x-transformers", "stars": 5942, "tags": ["transformers", "attention-mechanism", "pytorch", "research", "encoder-decoder", "gpt", "bert", "vision-transformer", "natural-language-processing", "gpu"], "topics": ["artificial-intelligence", "deep-learning", "attention-mechanism", "transformers"], "urls": [], "use_cases": ["build a gpt-style decoder-only transformer in pytorch", "implement an encoder-decoder transformer for seq2seq tasks", "experiment with new attention mechanisms from papers", "train a vision transformer for image classification", "prototype transformer architectures for research", "build an image captioning model"], "what_it_is": "A concise PyTorch library implementing full-attention transformer architectures (encoder, decoder, encoder-decoder, and vision transformers) with many experimental attention features drawn from recent research papers. It lets researchers and practitioners quickly assemble GPT-like, BERT-like, or ViT models with a few lines of code.", "when_to_avoid": ["you need a production-grade, optimized inference engine for large language models", "you want a full training framework with data pipelines, distributed training, and fine-tuning tooling", "you prefer batteries-included frameworks like Hugging Face Transformers with pretrained model hubs"], "when_to_choose": ["you want a lightweight, hackable transformer implementation for research or experimentation", "you need quick access to many experimental attention variants without writing them yourself", "you are prototyping custom architectures rather than serving production LLMs"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/x-transformers", "repo": "lucidrains/x-transformers", "role": "main", "score": 85}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:09:32.592859+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-29T17:50:45.927911+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f3615133a4b3e886dd46c6e51b5b212b818a09cda7e063819da55f6fada3f3b6", "fetched_at": "2026-08-28T04:09:32.592859+00:00", "kind": "readme", "missing": false, "url": "https://github.com/lucidrains/x-transformers"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:09:32.592859+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-29T17:50:45.927911+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f3615133a4b3e886dd46c6e51b5b212b818a09cda7e063819da55f6fada3f3b6", "fetched_at": "2026-08-28T04:09:32.592859+00:00", "kind": "readme", "missing": false, "url": "https://github.com/lucidrains/x-transformers"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-29T17:50:45.927911+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f3615133a4b3e886dd46c6e51b5b212b818a09cda7e063819da55f6fada3f3b6", "fetched_at": "2026-08-28T04:09:32.592859+00:00", "kind": "readme", "missing": false, "url": "https://github.com/lucidrains/x-transformers"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:09:32.592859+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:09:32.592859+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:09:32.592859+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-29T17:50:45.927911+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f3615133a4b3e886dd46c6e51b5b212b818a09cda7e063819da55f6fada3f3b6", "fetched_at": "2026-08-28T04:09:32.592859+00:00", "kind": "readme", "missing": false, "url": "https://github.com/lucidrains/x-transformers"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:09:32.592859+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:09:32.592859+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-29T17:50:45.927911+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f3615133a4b3e886dd46c6e51b5b212b818a09cda7e063819da55f6fada3f3b6", "fetched_at": "2026-08-28T04:09:32.592859+00:00", "kind": "readme", "missing": false, "url": "https://github.com/lucidrains/x-transformers"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:09:32.592859+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:09:32.592859+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:09:32.592859+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-29T17:50:45.927911+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f3615133a4b3e886dd46c6e51b5b212b818a09cda7e063819da55f6fada3f3b6", "fetched_at": "2026-08-28T04:09:32.592859+00:00", "kind": "readme", "missing": false, "url": "https://github.com/lucidrains/x-transformers"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:09:32.592859+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:09:32.592859+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-29T17:50:45.927911+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f3615133a4b3e886dd46c6e51b5b212b818a09cda7e063819da55f6fada3f3b6", "fetched_at": "2026-08-28T04:09:32.592859+00:00", "kind": "readme", "missing": false, "url": "https://github.com/lucidrains/x-transformers"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-29T17:50:45.927911+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f3615133a4b3e886dd46c6e51b5b212b818a09cda7e063819da55f6fada3f3b6", "fetched_at": "2026-08-28T04:09:32.592859+00:00", "kind": "readme", "missing": false, "url": "https://github.com/lucidrains/x-transformers"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-29T17:50:45.927911+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f3615133a4b3e886dd46c6e51b5b212b818a09cda7e063819da55f6fada3f3b6", "fetched_at": "2026-08-28T04:09:32.592859+00:00", "kind": "readme", "missing": false, "url": "https://github.com/lucidrains/x-transformers"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-29T17:50:45.927911+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f3615133a4b3e886dd46c6e51b5b212b818a09cda7e063819da55f6fada3f3b6", "fetched_at": "2026-08-28T04:09:32.592859+00:00", "kind": "readme", "missing": false, "url": "https://github.com/lucidrains/x-transformers"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 99, "longevity": 100, "rhythm": 58}, "computed_at": "2026-09-03T02:39:23.370411+00:00", "flags": [], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 2139, "days_push": 7, "days_rel": 202, "gap_med": 0.0, "n_releases_24m": 211}, "score": 85, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}