Ming-Image-0.1-Design Uyasebenza

I-Ming-Image-0.1-Design iyimodeli yokukhiqiza izithombe engu-6B evulekile yomthombo, ekhishwe yi-InclusionAI ye-Ant Group, egxile ezimweni zokuklama, esekela iziqondiso ezihlelekile ezinde ezifika ku-8K, futhi ekwazi ukukhiqiza ngokuphelele i-UI, ama-infographic, amaphosta neminye imiklamo ebonakalayo kusukela ekuqaleni kuze kube sekugcineni. Ihambisana nemodeli ye-Design-Layer nayo evulekile yomthombo, engahlukanisa umklamo ube izingqimba ezisobala ezingu-2—9 ezihlelekayo ngokuzimela, yenze kube khona inqubo ephelele yokukhiqiza—ukuhlukanisa izingqimba—ukuhlela—ukuletha. I-Ming-Image-0.1-Design ihamba phambili ohlwini lwamamodeli avulekile omthombo e-Artificial Analysis UI/UX, futhi isivele ihlanganiswe nezinsizakalo zangempela ezifana ne-Lingguang ne-Huamei.

Umbhalo uye emklamweni: Isekela iziqondiso ezihlelekile ezinde ezifika ku-8K, ikhiqize ngokuphelele imiklamo ye-UI, i-Dashboard, ama-infographic, amaphosta neminye imiklamo ebonakalayo kusukela ezidingweni zombhalo.
Ukuhunyushwa kombhalo nokwakheka: Ithuthukisa ukuvezwa kwezihloko, izinkinobho, amakhadi nolwazi olunezindawo eziningi, iqinisekise ukuma okuzinzile nokuhlelwa kolwazi okunembile.
Ukuvumelana kwesitayela sonke: Iqedela wonke umklamo ngesikhathi esisodwa, ihlanganise imibala, ukwakheka kanye nesitayela sezinto, igweme ukungahambisani kwesitayela okubangelwa ukukhiqiza kaningi.
Ukukhiqizwa kwezinto ezisobala: I-RGBA VAE yomdabu ikhiqiza ngokuqondile izinto ezinezizinda ezisobala, njengabantu, imikhiqizo, izithonjana nemihlobiso.
Ukuhlukanisa umklamo ube izingqimba (Layer): Ihlukanisa umklamo ube izingqimba ze-RGBA ezingu-2—9 ezizimele ngokwencazelo, isekele ukuhlela, ukuhambisa nokushintsha umbhalo, into eyinhloko nesizinda ngokwehlukana.
Ukulethwa kwe-frontend (Design Skill): I-Text-to-Page iqala ngohlelo lomklamo bese ibhala ikhodi, kanti i-Visual Coding isekela ukubuyisela isithombe-skrini somklamo sibe ikhasi elisebenzayo.
Ukulethwa kwe-PPT (PPT Skill): Ibuyisela umbhalo, izindawo ezinemibala nokwakheka kwesithombe kube izakhi ze-PowerPoint ezihlelekayo, futhi ikhiphe izithonjana nemifanekiso ukuze kusetshenziswe kabusha.

Landela i-WeChat bese uphendula ngokuthi “开源” ukuze ujoyine iqembu lezingxoxo zamaphrojekthi e-AI avulekile
Ukuqiniswa kweziqondiso ezihlelekile ezinde ze-8K: Imodeli ihlela ngokuzenzakalelayo izidingo zomsebenzisi zibe okokubhala, amamojuli, ukwakheka nesitayela esibonakalayo, ukuze ulwazi oluseziqondisweni ezinde kakhulu, ezifika ku-8K, luqondwe futhi lusetshenziswe ngokuphelele, isekele ukuvezwa okunembile kwamamojuli nezinto eziningi emakhasini ayinkimbinkimbi.
Ukukhiqizwa komklamo ophelele kusukela ekuqaleni kuze kube sekugcineni: Ngokungafani nendlela yokukhiqiza isizinda, imifanekiso nemihlobiso ngokwehlukana bese uyihlanganisa, imodeli ilawula ukwakheka konke, imibala nesitayela sezinto ngesikhathi esisodwa sokukhiqiza. Ukuqeqeshwa okukhethekile kuqinisa ikhono lombhalo, ukwakheka nokuhlanganiswa kwezinto eziningi, kunciphisa kakhulu ukungqubuzana kwemibala nokungahambisani kwesitayela phakathi kwezinto.
I-RGBA VAE yomdabu: Imodeli inekhodi ezenzakalelayo ehlukile esekela isiteshi se-Alpha, okwenza indawo yokukhiqiza ihlanganise ngokuqondile izinto ezinezizinda ezisobala. Abantu, imikhiqizo, izithonjana nemihlobiso kungakhishwa nesiteshi se-Alpha esisobala, ngaphandle kwesidingo sokususa isizinda ngemva kwalokho.
Ukulawulwa kwendima yezingqimba nge-Type Token: Imodeli ye-Layer itshela ngokusobala ingqimba ngayinye indima yayo yokuklama nge-Type Token, iqondise imodeli ukuthi ihlukanise ngokwencazelo futhi iqinisekise ukuthi okuqukethwe kwezingqimba ezikhishiwe kucacile, nemisebenzi yazo izimele.
Ukuthuthukiswa kwe-Alpha-Aware Layer: Kwenziwa ukuthuthukiswa okukhethekile ezindaweni ezisobala nasemiphethweni, kugxilwe ekunembeni kwesiteshi se-Alpha ezingqimbeni ze-RGBA, ukuze imiphetho esobala ihlanzeke futhi ingabi nezinsalela, kuxazululwe ukufiphala kwemiphetho noma ukuxubana nombala wesizinda lapho ukufihla kuyinkimbinkimbi.
Composite-Layer Stack Consistency (umkhawulo wokuvumelana wokuhlanganisa kabusha): Ngesikhathi sokuqeqeshwa, kuyaphoqelelwa ukuthi zonke izingqimba ezihlukanisiwe zikwazi ukuphinde zihlanganiswe zibuyisele umklamo wokuqala, kulawulwe ukuvumelana kobudlelwane bendawo nokugcwaliswa kwezindawo ezifihlekile phakathi kwezingqimba.

Khetha indlela yokuyisebenzisa: Ungayizama ngokushesha nge-API yamahhala ye-OpenRouter ku-inthanethi https://openrouter.ai/inclusionai/ming-image-0.1-design, noma ulande izisindo zemodeli ku-Hugging Face / ModelScope ukuze uyifake endaweni yakho.
Bhala iziqondiso: Chaza izidingo ngolimi lwemvelo; kunconywa ukuhlela okuqukethwe ngokwesakhiwo “okokubhala, amamojuli, ukwakheka, isitayela esibonakalayo” ukuze usebenzise ngokugcwele amandla eziqondiso ezinde ze-8K.
Khiqiza umklamo: Shayela imodeli ye-Design ukuze ukhiqize ngesikhathi esisodwa umklamo ophelele we-UI, i-infographic noma iphosta.
Hlukanisa izingqimba: Faka umklamo okhiqiziwe noma okhona kumodeli ye-Design-Layer ukuze uwuhlukanise ube izingqimba ezisobala ezingu-2—9 ezihlelekayo ngokuzimela.
Ukulethwa kwe-frontend: Thola i-Design Skill (ling-cookbook) ku-GitHub; faka izidingo ukuze uthole uhlelo lwekhasi cishe ngemizuzwana engu-15, bese ngemva kokuqinisekisa uludlulisele ku-Coding ukuze kukhiqizwe ikhasi elisebenzayo.
Ukulethwa kwe-PPT: Sebenzisa i-PPT Skill (ling-cookbook) ukuze ubuyisele umklamo ngokuchofoza okukodwa ube ikhasi le-PowerPoint elihlelekayo, bese uqhubeka nokuhlela okokubhala, imibala nokwakheka.

Amapharamitha amancane, ukusebenza okuphezulu: Amapharamitha angu-6B adlula amamodeli amakhulu afana ne-Nano Banana 2 ne-FLUX.2; emisebenzini eyinkimbinkimbi ye-UI iwina yonke imijikelezo engu-12/12 no-10/10.
Ukuvumelana kwesitayela kusukela ekuqaleni kuze kube sekugcineni: Ilawula ukwakheka, imibala nezinto ngesikhathi esisodwa, igweme ukungahambisani kwesitayela nomuzwa wethempulethi obangelwa ukuhlanganisa imiphumela ekhiqizwe kaningi.
Umklamo uyahleleka: Imodeli ye-Layer ihlukanisa umklamo ube izingqimba ze-RGBA ezizimele ngokwencazelo; ithola indawo yokuqala kuzo zonke izinkomba ezingu-12 ze-Crello-Test, okwenza imiphumela ekhiqiziwe iqhubeke nokuhlelwa.
Ijubane eliphezulu nezindleko eziphansi: Ishesha ngokuphindwe ka-4.3 kunenguqulo evulekile ye-Qwen engu-20B; ngemva kokuthuthukiswa kobunjiniyela, ikhiqiza isithombe cishe ngemizuzwana engu-20, kanti izindleko zokushintsha umbhalo zingokungu-1/7 kuphela kwezika-GPT-image2.
Uchungechunge lokuletha oluphelele: Ngokuhambisana ne-Design Skill ne-PPT Skill, ingadlula ngokuqondile embhalweni noma esithombeni sereferensi iye ekhasini le-frontend ne-PPT elihlelekayo; isikhathi sokubona umphumela wokuqala sehle sisuka emizuzwini emi-5 saya kumasekhondi angu-15.
Izidingo zokufaka eziphansi: Inani lamapharamitha angu-6B lehlisa izindleko zokufaka nokuthuthukisa kabusha; izisindo nama-Skill konke kuvulekile, kusekela ukwakhiwa kwamathuluzi okuklama ngokukhululeka.

Umtapo wamamodeli we-HuggingFace: https://huggingface.co/inclusionAI/Ming-Image-0.1-Design
https://huggingface.co/inclusionAI/Ming-Image-0.1-Design-Layer

Ukubuka kuqala kokukhiqizwa kwezinhlelo ze-AI: Ngaphambi kokuthi i-Agent ibhale ikhodi, i-Design iqala ikhiqize ukubuka kuqala okubonakalayo kohlelo, ukuze umsebenzisi aqinisekise indlela kusenesikhathi futhi athole “okubonayo yilokho okutholayo”.
Ukuhlela izingqimba zemiklamo yobungcweti: Hlukanisa iphosta noma isithombe esiyinhloko se-e-commerce ngokuchofoza okukodwa sibe izingqimba ezihlelekayo; umklami angashintsha umbhalo, ahambise into eyinhloko, ashintshe isizinda futhi akhiphe i-PSD cishe ngemizuzwana engu-40.
Ukubuyiselwa kwekhasi le-frontend (Visual Coding): Faka umklamo noma isithombe-skrini; ngemva kokuhlukanisa izinto nge-Layer, kukhiqizwa ngokuzenzakalelayo ikhasi le-frontend elisebenzayo, bese liqinisekiswa futhi lilungiswe ngokuzenzakalelayo ngokuqhathanisa izithombe-skrini.
Ukukopishwa okusheshayo kwe-PPT: Buyisela umklamo owodwa ube ikhasi le-PowerPoint elihlelekayo; okokubhala, imibala nezithombe konke kungaqhubeka nokuhlelwa, futhi izithonjana nemifanekiso kukhishwa ukuze kusetshenziswe kabusha.