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STune-A-Video
[ICCV 2023] Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation
Popularity
Repository stars5,112Highest4,359
7-day net stars——
Fork413Highest388
30-day trendInsufficient historyInsufficient history
Maintenance
Last push2026-01-092023-10-25
Maintenance notesNot verifiedNot verified
Repository created2023-04-032022-12-25
License & use
LicenseLicense not declaredApache-2.0 · Permissive
PricingPricing not verifiedPricing not verified
Basics
Browse by purposeAI & agentsAI & agents
TypeModels & adaptersModels & adapters
SubcategoryVideo modelsVideo models
PlatformNot verifiedNot verified
Cost detailsCheck current official software, hosting, model and infrastructure pricing.Check current official software, hosting, model and infrastructure pricing.
Pricing source——
First collected2026-11-032026-11-03
MetricRepository stars, not unique users or individual-skill installsRepository stars, not unique users or individual-skill installs
LanguagePythonPython
About this projectVideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models[ICCV 2023] Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation
Measured at2026-11-03 08:31 UTC2026-11-03 09:37 UTC
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