{"adoption": {"forks": 6781, "observed_at": "2026-08-28T04:12:21.483761+00:00", "stars": 74883}, "canonical_url": "https://ross.abutalabs.com/products/unsloth", "card": {"archived": false, "artifact_type": "application", "description": "Local UI to run and train LLMs and diffusion models, including Qwen3.8, Kimi K3, MiniMax-H3, Gemma 4, DeepSeek-V4, FLUX and more.", "domain": ["large-language-models", "machine-learning", "deep-learning", "artificial-intelligence", "image-processing", "speech-processing"], "enriched": true, "function": ["llm-inference", "llm-training", "machine-learning", "stable-diffusion", "tts", "agent-framework", "gui"], "health_score": 100, "homepage": "https://unsloth.ai/docs", "language": "Python", "license": "Apache-2.0", "license_family": "permissive", "maturity": "active", "member_repos": ["unslothai/unsloth", "unslothai/notebooks"], "name": "Unsloth", "platform": ["windows", "python"], "pushed_at": "2026-08-27T00:28:18+00:00", "repo": "unslothai/unsloth", "stars": 74883, "tags": ["fine-tuning", "desktop-app", "local-llm", "diffusion-models", "qlora", "self-hosted", "multi-gpu", "macos", "linux", "desktop", "gpu"], "topics": ["fine-tuning", "llama", "llms", "gemma", "unsloth", "llm", "deepseek", "text-to-speech", "tts", "qwen", "agent", "openai", "reinforcement-learning", "self-hosted", "ui", "image-generation", "stable-diffusion", "chatgpt", "ai", "python"], "urls": [], "use_cases": ["fine-tune llama or qwen models locally", "run deepseek and gemma models on my own gpu", "train a stable diffusion or flux image model", "fine-tune an llm with a gui without writing code", "run reinforcement learning training for llms", "self-host a chatgpt-like assistant", "fine-tune text-to-speech models"], "what_it_is": "Unsloth is a desktop application for running and fine-tuning LLMs, diffusion, embedding, and audio models locally, with support for NVIDIA, AMD, Intel GPUs, CPUs, and Vulkan. It also provides a Python library and free notebooks for fast model fine-tuning.", "when_to_avoid": ["you need a headless server-side inference API at scale", "you only want cloud-hosted model training", "you need non-Python tooling"], "when_to_choose": ["you want a desktop UI to run and train models locally", "you need fast fine-tuning with limited GPU memory", "you want multi-GPU and multi-vendor GPU support", "you prefer ready-made training notebooks"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/repos/unslothai/unsloth", "repo": "unslothai/unsloth", "role": "main", "score": 94}, {"path": "/repos/unslothai/notebooks", "repo": "unslothai/notebooks", "role": "examples", "score": 66}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:12:21.483761+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-29T16:14:48.053012+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "a3536339916ec911dc36c9b318d90db1d41fdb1b04264d18c64254cba09f48d5", "fetched_at": "2026-08-28T04:12:21.483761+00:00", "kind": "readme", "missing": false, "url": "https://github.com/unslothai/unsloth"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:12:21.483761+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-29T16:14:48.053012+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "a3536339916ec911dc36c9b318d90db1d41fdb1b04264d18c64254cba09f48d5", "fetched_at": "2026-08-28T04:12:21.483761+00:00", "kind": "readme", "missing": false, "url": "https://github.com/unslothai/unsloth"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-29T16:14:48.053012+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "a3536339916ec911dc36c9b318d90db1d41fdb1b04264d18c64254cba09f48d5", "fetched_at": "2026-08-28T04:12:21.483761+00:00", "kind": "readme", "missing": false, "url": "https://github.com/unslothai/unsloth"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:12:21.483761+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:12:21.483761+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:12:21.483761+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-29T16:14:48.053012+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "a3536339916ec911dc36c9b318d90db1d41fdb1b04264d18c64254cba09f48d5", "fetched_at": "2026-08-28T04:12:21.483761+00:00", "kind": "readme", "missing": false, "url": "https://github.com/unslothai/unsloth"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:12:21.483761+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:12:21.483761+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-29T16:14:48.053012+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "a3536339916ec911dc36c9b318d90db1d41fdb1b04264d18c64254cba09f48d5", "fetched_at": "2026-08-28T04:12:21.483761+00:00", "kind": "readme", "missing": false, "url": "https://github.com/unslothai/unsloth"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:12:21.483761+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:12:21.483761+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:12:21.483761+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-29T16:14:48.053012+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "a3536339916ec911dc36c9b318d90db1d41fdb1b04264d18c64254cba09f48d5", "fetched_at": "2026-08-28T04:12:21.483761+00:00", "kind": "readme", "missing": false, "url": "https://github.com/unslothai/unsloth"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:12:21.483761+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:12:21.483761+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-29T16:14:48.053012+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "a3536339916ec911dc36c9b318d90db1d41fdb1b04264d18c64254cba09f48d5", "fetched_at": "2026-08-28T04:12:21.483761+00:00", "kind": "readme", "missing": false, "url": "https://github.com/unslothai/unsloth"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-29T16:14:48.053012+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "a3536339916ec911dc36c9b318d90db1d41fdb1b04264d18c64254cba09f48d5", "fetched_at": "2026-08-28T04:12:21.483761+00:00", "kind": "readme", "missing": false, "url": "https://github.com/unslothai/unsloth"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-29T16:14:48.053012+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "a3536339916ec911dc36c9b318d90db1d41fdb1b04264d18c64254cba09f48d5", "fetched_at": "2026-08-28T04:12:21.483761+00:00", "kind": "readme", "missing": false, "url": "https://github.com/unslothai/unsloth"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-29T16:14:48.053012+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "a3536339916ec911dc36c9b318d90db1d41fdb1b04264d18c64254cba09f48d5", "fetched_at": "2026-08-28T04:12:21.483761+00:00", "kind": "readme", "missing": false, "url": "https://github.com/unslothai/unsloth"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 99, "longevity": 72, "rhythm": 99}, "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": 1008, "days_push": 7, "days_rel": 8, "gap_med": 6.5, "n_releases_24m": 53}, "score": 94, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}