{"adoption": {"forks": 192, "observed_at": "2026-08-28T04:04:46.145754+00:00", "stars": 1452}, "canonical_url": "https://ross.abutalabs.com/products/neuronblocks", "card": {"archived": false, "artifact_type": "framework", "description": "NLP DNN Toolkit - Building Your NLP DNN Models Like Playing Lego", "domain": ["deep-learning", "machine-learning"], "enriched": true, "function": ["machine-learning", "deep-learning", "nlp", "llm-training"], "health_score": 20, "homepage": null, "language": "Python", "license": "MIT", "license_family": "permissive", "maturity": "maintenance", "member_repos": ["microsoft/NeuronBlocks"], "name": "microsoft/NeuronBlocks", "platform": ["python", "windows", "cross-platform"], "pushed_at": "2023-07-22T03:07:55+00:00", "repo": "microsoft/NeuronBlocks", "stars": 1452, "tags": ["pytorch", "model-zoo", "block-zoo", "-configuration", "knowledge-distillation", "model-compression", "sequence-labeling", "text-classification", "question-answering", "natural-language-processing", "linux"], "topics": ["question-answering", "deep-learning", "pytorch", "natural-language-processing", "text-classification", "artificial-intelligence", "dnn", "qna", "text-matching", "knowledge-distillation", "model-compression", "sequence-labeling"], "urls": [], "use_cases": ["build nlp deep learning models without writing code", "train a text classifier with  config", "do sequence labeling like slot tagging", "train a question answering matching model", "compress models via knowledge distillation", "prototype neural architectures from reusable blocks"], "what_it_is": "NeuronBlocks is an NLP deep learning modeling toolkit from Microsoft that lets users build end-to-end neural network training and inference pipelines for NLP tasks using composable blocks and JSON configuration files. It includes a Block Zoo of reusable neural components and a Model Zoo of prebuilt models for tasks like classification, sequence labeling, and question answering matching.", "when_to_avoid": ["you need state-of-the-art transformer fine-tuning with modern ecosystems like Hugging Face", "you require active community support or frequent updates", "you work outside NLP or need non-PyTorch frameworks"], "when_to_choose": ["you want config-driven NLP model training in PyTorch", "you need prebuilt models for common NLP tasks like classification or slot tagging", "you want to experiment with model architectures by composing blocks"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/neuronblocks", "repo": "microsoft/NeuronBlocks", "role": "main", "score": 23}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:04:46.145754+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T04:35:49.011071+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7dc552303475199d02760011823c80eb039cd99b71beff6bcc382dacff2ef84a", "fetched_at": "2026-08-28T04:04:46.145754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/microsoft/NeuronBlocks"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:04:46.145754+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T04:35:49.011071+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7dc552303475199d02760011823c80eb039cd99b71beff6bcc382dacff2ef84a", "fetched_at": "2026-08-28T04:04:46.145754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/microsoft/NeuronBlocks"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T04:35:49.011071+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7dc552303475199d02760011823c80eb039cd99b71beff6bcc382dacff2ef84a", "fetched_at": "2026-08-28T04:04:46.145754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/microsoft/NeuronBlocks"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:04:46.145754+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:04:46.145754+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:04:46.145754+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T04:35:49.011071+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7dc552303475199d02760011823c80eb039cd99b71beff6bcc382dacff2ef84a", "fetched_at": "2026-08-28T04:04:46.145754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/microsoft/NeuronBlocks"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:04:46.145754+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:04:46.145754+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T04:35:49.011071+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7dc552303475199d02760011823c80eb039cd99b71beff6bcc382dacff2ef84a", "fetched_at": "2026-08-28T04:04:46.145754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/microsoft/NeuronBlocks"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:04:46.145754+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:04:46.145754+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:04:46.145754+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T04:35:49.011071+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7dc552303475199d02760011823c80eb039cd99b71beff6bcc382dacff2ef84a", "fetched_at": "2026-08-28T04:04:46.145754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/microsoft/NeuronBlocks"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:04:46.145754+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:04:46.145754+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T04:35:49.011071+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7dc552303475199d02760011823c80eb039cd99b71beff6bcc382dacff2ef84a", "fetched_at": "2026-08-28T04:04:46.145754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/microsoft/NeuronBlocks"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T04:35:49.011071+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7dc552303475199d02760011823c80eb039cd99b71beff6bcc382dacff2ef84a", "fetched_at": "2026-08-28T04:04:46.145754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/microsoft/NeuronBlocks"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T04:35:49.011071+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7dc552303475199d02760011823c80eb039cd99b71beff6bcc382dacff2ef84a", "fetched_at": "2026-08-28T04:04:46.145754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/microsoft/NeuronBlocks"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T04:35:49.011071+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7dc552303475199d02760011823c80eb039cd99b71beff6bcc382dacff2ef84a", "fetched_at": "2026-08-28T04:04:46.145754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/microsoft/NeuronBlocks"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 0, "longevity": 100, "rhythm": 8}, "computed_at": "2026-09-03T02:20:16.233290+00:00", "flags": [], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 2698, "days_push": 1138, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 23, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}