{"adoption": {"forks": 112, "observed_at": "2026-08-28T04:04:26.080375+00:00", "stars": 1340}, "canonical_url": "https://ross.abutalabs.com/products/beyond-nanogpt", "card": {"archived": false, "artifact_type": "learning-resource", "description": "Minimal and annotated implementations of key ideas from modern deep learning research. ", "domain": ["deep-learning", "large-language-models", "machine-learning", "education", "tutorials"], "enriched": true, "function": ["machine-learning", "deep-learning", "llm-training", "reinforcement-learning", "llm-inference", "stable-diffusion", "gpu-computing"], "health_score": 59, "homepage": null, "language": "Python", "license": "MIT", "license_family": "permissive", "maturity": "active", "member_repos": ["tanishqkumar/beyond-nanogpt"], "name": "tanishqkumar/beyond-nanogpt", "platform": ["python", "cross-platform"], "pushed_at": "2026-01-29T07:09:42+00:00", "repo": "tanishqkumar/beyond-nanogpt", "stars": 1340, "tags": ["educational", "from-scratch-implementations", "nanogpt", "annotated-code", "transformers", "diffusion-models", "research-education", "gpu"], "topics": [], "urls": [], "use_cases": ["learn how transformers and LLMs work from scratch", "understand KV caching and speculative decoding implementations", "study diffusion models and flow matching with minimal code", "learn reinforcement learning algorithms like PPO from scratch", "prepare to do deep learning research after learning basics", "understand tensor parallelism and GPU communication", "implement attention variants like linear attention myself"], "what_it_is": "An educational repository of minimal, annotated, from-scratch implementations of ~100 modern deep learning techniques, bridging nanoGPT and research-level work. It covers LLM techniques, attention variants, generative models, reinforcement learning, and GPU systems fundamentals, all runnable on a single GPU.", "when_to_avoid": ["you need production-ready, optimized model implementations", "you want a maintained library or framework to build applications on", "you need multi-node distributed training support", "you're looking for a plug-and-play model zoo"], "when_to_choose": ["you want annotated, from-scratch implementations to learn deep learning deeply", "you're moving from beginner LLM tutorials toward research-level understanding", "you want single-GPU runnable reference code for modern techniques", "you prefer reading and hacking on minimal code over heavy frameworks"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/beyond-nanogpt", "repo": "tanishqkumar/beyond-nanogpt", "role": "main", "score": 48}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:04:26.080375+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T04:43:52.946510+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "ec3f4d706ef4ee16a17e6143a6b88c57d3c4a7d4be9d5a7aedd71186806be899", "fetched_at": "2026-08-28T04:04:26.080375+00:00", "kind": "readme", "missing": false, "url": "https://github.com/tanishqkumar/beyond-nanogpt"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:04:26.080375+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T04:43:52.946510+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "ec3f4d706ef4ee16a17e6143a6b88c57d3c4a7d4be9d5a7aedd71186806be899", "fetched_at": "2026-08-28T04:04:26.080375+00:00", "kind": "readme", "missing": false, "url": "https://github.com/tanishqkumar/beyond-nanogpt"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T04:43:52.946510+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "ec3f4d706ef4ee16a17e6143a6b88c57d3c4a7d4be9d5a7aedd71186806be899", "fetched_at": "2026-08-28T04:04:26.080375+00:00", "kind": "readme", "missing": false, "url": "https://github.com/tanishqkumar/beyond-nanogpt"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:04:26.080375+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:04:26.080375+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:04:26.080375+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T04:43:52.946510+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "ec3f4d706ef4ee16a17e6143a6b88c57d3c4a7d4be9d5a7aedd71186806be899", "fetched_at": "2026-08-28T04:04:26.080375+00:00", "kind": "readme", "missing": false, "url": "https://github.com/tanishqkumar/beyond-nanogpt"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:04:26.080375+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:04:26.080375+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T04:43:52.946510+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "ec3f4d706ef4ee16a17e6143a6b88c57d3c4a7d4be9d5a7aedd71186806be899", "fetched_at": "2026-08-28T04:04:26.080375+00:00", "kind": "readme", "missing": false, "url": "https://github.com/tanishqkumar/beyond-nanogpt"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:04:26.080375+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:04:26.080375+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:04:26.080375+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T04:43:52.946510+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "ec3f4d706ef4ee16a17e6143a6b88c57d3c4a7d4be9d5a7aedd71186806be899", "fetched_at": "2026-08-28T04:04:26.080375+00:00", "kind": "readme", "missing": false, "url": "https://github.com/tanishqkumar/beyond-nanogpt"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:04:26.080375+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:04:26.080375+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T04:43:52.946510+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "ec3f4d706ef4ee16a17e6143a6b88c57d3c4a7d4be9d5a7aedd71186806be899", "fetched_at": "2026-08-28T04:04:26.080375+00:00", "kind": "readme", "missing": false, "url": "https://github.com/tanishqkumar/beyond-nanogpt"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T04:43:52.946510+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "ec3f4d706ef4ee16a17e6143a6b88c57d3c4a7d4be9d5a7aedd71186806be899", "fetched_at": "2026-08-28T04:04:26.080375+00:00", "kind": "readme", "missing": false, "url": "https://github.com/tanishqkumar/beyond-nanogpt"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T04:43:52.946510+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "ec3f4d706ef4ee16a17e6143a6b88c57d3c4a7d4be9d5a7aedd71186806be899", "fetched_at": "2026-08-28T04:04:26.080375+00:00", "kind": "readme", "missing": false, "url": "https://github.com/tanishqkumar/beyond-nanogpt"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T04:43:52.946510+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "ec3f4d706ef4ee16a17e6143a6b88c57d3c4a7d4be9d5a7aedd71186806be899", "fetched_at": "2026-08-28T04:04:26.080375+00:00", "kind": "readme", "missing": false, "url": "https://github.com/tanishqkumar/beyond-nanogpt"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 64, "longevity": 36, "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": 504, "days_push": 216, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 48, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}