Model
.ai
追蹤開放 AI 模型
建立者
Lykon
(Civitai)
Dreamshaper 8 by Lykon is one of the most popular base models for illustrations and art. This update includes better support for character LoRAs, better photorealism, can still handle anime, and better NSFW
創作者說明
DreamShaper - V∞! Please check out my other , including SDXL ones! Check the version description below (bottom right) for more info and add a ❤️ to receive future updates. Do you like what I do? Consider supporting me on 🅿️ to get exclusive tips and tutorials, or feel free to ☕ 🎟️ Join my For LCM read the version description. Available on the following websites with GPU acceleration: - - - - - - (CPU is slow but free). New Negative Embedding for this: . Message from the author Hello hello, my fellow AI Art lovers. Version 8 just released. Did you like the cover with the ∞ symbol? This version holds a special meaning for me. DreamShaper started as a model to have an alternative to MidJourney in the open source world. I didn't like how MJ was handled back when I started and how closed it was and still is, as well as the lack of freedom it gives to users compared to SD. Look at all the tools we have now from TIs to LoRA, from ControlNet to Latent Couple. We can do anything. The purpose of DreamShaper has always been to make "a better Stable Diffusion", a model capable of doing everything on its own, to weave dreams. With SDXL (and, of course, DreamShaper XL 😉) just released, I think the "swiss knife" type of model is closer then ever. That model architecture is big and heavy enough to accomplish that the pretty easily. But what about all the resources built on top of SD1.5? Or all the users that don't have 10GB of vram? It might just be a bit too early to let go of DreamShaper. Not before one. Last. Push. And here it is, I hope you enjoy. And thank you for all the support you've given me in the recent months. PS: the primary goal is still towards art and illustrations. Being good at everything comes second. Suggested settings: - I had CLIP skip 2 on some pics, the model works with that too. - I have ENSD set to 31337, in case you need to reproduce some results, but it doesn't guarantee it. - All of them had highres.fix or img2img at higher resolution. Some even have ADetailer. Careful with that tho, as it tends to make all faces look the same. - I don't use "restore faces". For old versions: - Versions >4 require no LoRA for anime style. For version 3 I suggest to use one of these LoRA networks at 0.35 weight: -- (the girls with glasses or if it says wanostyle) -- (if it says mksk style) -- (not used for any example but works great). LCM Being a distilled model it has lower quality compared to the base one. However it's MUCH faster and perfect for video and real time applications. Use it with 5-15 steps, ~2 cfg. IT WORKS ONLY WITH LCM SAMPLER (as of December 2023, Auto1111 requires an external plugin for it). Comparison with V7 LCM NOTES - Version 8 focuses on improving what V7 started. Might be harder to do photorealism compared to realism focused models, as it might be hard to do anime compared to anime focused models, but it can do both pretty well if you're skilled enough. Check the examples! - Version 7 improves lora support, NSFW and realism. If you're interested in "absolute" realism, try . - Version 6 adds more lora support and more style in general. It should also be better at generating directly at 1024 height (but be careful with it). 6.x are all improvements. - Version 5 is the best at photorealism and has noise offset. - Version 4 is much better with anime (can do them with no LoRA) and booru tags. IT might be harder to control if you're used to caption style, so you might still want to use version 3.31. - V4 is also better with eyes at lower resolutions. Overall is like a "fix" of V3 and shouldn't be too much different. - Results of version 3.32 "clip fix" will vary from the examples (produced on 3.31, which I personally prefer). - I get no money from any generative service, but you can buy me a coffee. - You should use 3.32 for mixing, so the clip error doesn't spread. - Inpainting models are only for inpaint and outpaint, not txt2img or mixing. Original v1 description: After a lot of tests I'm finally releasing my mix model. This started as a model to make good portraits that do not look like cg or photos with heavy filters, but more like actual paintings. The result is a model capable of doing portraits like I wanted, but also great backgrounds and anime-style characters. Below you can find some suggestions, including LoRA networks to make anime style images. I hope you'll enjoy it as much as I do. Official HF repository:
Civitai 上 1,083,161 次下載 · 18,255 個讚
SHA256
879DB523C30D3B9017143D56705015E15A2CB5628762C11D086FED9538ABD7FD
DreamShaper 熱度趨勢
熱度分數,過去 12 個月
熱度分數
9,440°
本週
▼
0.5%
9,442° 當時,9,440° 現在
本月
▼
2.0%
9,451° 當時,9,440° 現在
過去一年
▼
24.6%
9,575° 當時,9,440° 現在
DreamShaper: 熱度分數,過去 12 個月7,000°7,854°8,707°9,561°10,415°Oct 2025Dec 2025Mar 2026May 2026Aug 2026Oct 20269,440°ModelTrends.ai
7,000°
基準值
分數範圍是從 0° 到 9,999°。低於 7,000° 的部分是留給還沒被任何來源報告的模型,它們會有一個替代數字,讓列表保持完整。7,000° 是有測量數據開始的地方:有真實數據但幾乎沒下載的模型會在基準值,之後的度數才是測量結果。基準值本身不代表模型好壞,只有基準值以上的度數才會區分模型。
+379°
Civitai 下載量
此版本在 Civitai 上有 1,083,161 次下載。下載量是最重要的成分,且以對數刻度計算:下載量增加十倍,熱度增加 300°,因此一百萬下載的模型不會比一千下載的熱度高一千倍。六個下載來源共用此一項,依其數量比例分配。
+3°
種子用戶數
有 8 人透過種子或鏡像持續分享權重檔案。分享檔案需要實際頻寬,代表權重仍有人需求,所以每個種子用戶相當於下載量中的 1,000 次。
+1,643°
AI Horde 生成圖像數
志願者 AI Horde 用這個模型生成了 4,684,387 張圖。每張圖算作一次下載,使用量和下載量一樣重要。
+7°
生成網站數
這個模型在 PixAI 上的複製品有 20,237 次下載和生成執行。每次執行算一次下載,下載計算方式和 Civitai 一樣;這些都合併計入下載項目。
+641°
喜歡數
各來源共有 18,679 個喜歡和讚。每個喜歡相當於半次下載,採用同樣的對數刻度。
+226°
採用率
大約每天 1,027 次下載,根據兩次來源讀取間的變化計算,不是用整個生命週期平均。速度佔下載項目的四分之一,能反映新熱潮,但不會讓一天的爆量超過多年累積。
+150°
完整模型
+150° 因為這是完整模型:檢查點,也就是權重本身。LoRA 或嵌入是別人權重的附加,不會比同人氣的檢查點更熱。
−609°
年齡
−609° 因為 SD15 權重是在 2022 發布的。每個模型都繼承它所用權重的年齡:每年扣 150°,最多扣 750°,扣分會持續增加。沒有這項,排行榜頂端會是 2022 和 2023 年的檢查點,因為下載有多年累積。
顯示詳細分析
這個網站上的每個數字都可以查證。這個模型的熱度分數是 9,440°,這裡會一步步拆解它的組成,每加一項就會顯示目前的總分:基準值、每個來源增加的度數、模型類型的加分,以及權重年齡帶來的扣分。顏色對應上方圖表的區間。最後的詞彙表會解釋每個術語。
  1. 1
    從基準值開始。
    為什麼是 7,000° 而不是零:分數範圍是 0° 到 9,999°,低於 7,000° 的部分是留給還沒被任何來源報告的模型,它們有替代數字,讓列表完整且不會超過有數據的模型。7,000° 是有測量數據開始的地方。有真實數據但幾乎沒下載的模型會在這裡;之後的度數是測量結果,基準值以上有十個十倍下載的階段,每階段增加 300°。基準值對所有模型都一樣,不會決定排名;真正區分模型的是基準值以上的度數。
    7,000°
    累計總和
  2. 2
    加入下載量。
    總共 5,795,785 個下載等值,來自 Civitai 下載量, 種子用戶數, AI Horde 生成圖像數, 生成網站數。下載量增加十倍會增加相同的 300°,所以大小很重要,但不會主導分數。
    +379° Civitai 下載量
    +3° 種子用戶數
    +1,643° AI Horde 生成圖像數
    +7° 生成網站數
    +2,032°
    9,032°
    累計總和
  3. 3
    加入喜歡數。
    18,679 個喜歡和讚,權重是下載量的一半。
    +641°
    9,673°
    累計總和
  4. 4
    加入採用率。
    目前大約每天 1,027 次下載,根據兩次讀取間的差異計算,權重是下載量的四分之一。
    +226°
    9,899°
    累計總和
  5. 5
    完整模型的額外加分。
    檢查點包含權重本身;附加元件不會超過同樣受歡迎度的完整模型。
    +150°
    10,049°
    累計總和
  6. 6
    移除年齡。
    SD15 權重於 2022 發布:每年扣除 150°,最多扣除 750°,直到達到上限。
    −609°
    9,440°
    累計總和
  7. =
    熱度分數。
    這個模型在本網站所有排行榜上的位置。沒有其他因素會調整它。
    9,440°
詞彙表:這裡使用的術語
熱度分數
一個數字,表示模型目前的使用和需求程度,範圍從 0° 到 9,999°。本網站所有標示「最熱門」的排行榜都是依此排序,沒有其他排序依據。
底線
每個有實際數據的模型起始於 7,000°。分數範圍是 0° 到 9,999°;底線以下保留給沒有數據的模型,確保有數據的模型總是排名較前。底線對所有人相同,不影響排名;超過底線的度數才是評分依據。
下載等值
分數中視為下載的所有項目加總:下載本身、每個種子節點算 1,000、每張 AI Horde 圖像和每次生成網站的執行算一。
對數刻度
以十為單位計數,不是以一為單位:從 1,000 到 10,000 下載增加的度數,和從 10,000 到 100,000 增加的度數相同。這樣能防止巨頭壓過其他模型。
喜歡數
來自各來源的讚和喜歡,每個在對數刻度上算半個下載量。
採用率
模型目前每天的下載次數,根據兩次來源讀取的差異計算。權重是下載量的四分之一。
實測與估算
實測表示有兩個來源的讀數,且差異是真實的。估算表示只知道今天的總數,過去的數據則分散在模型的整個生命週期;網站會說明顯示的是哪一種。
種子節點
指在線上保留權重檔案供他人透過種子下載的人,或是提供相同服務的鏡像站。每一個種子節點算作1,000次下載。
AI Horde
一個志願者網絡,利用捐贈的電腦免費生成圖片。它用某模型生成的圖片數量是公開的,每張圖片算作一次下載。
生成網站
自己托管模型並讓人使用它生成圖片的網站,例如PixAI、SeaArt和Yodayo。它們的下載量和Civitai一樣,每次生成算一次下載。
OpenRouter 代幣
透過 API 提供的文字模型,如 Claude 或 GPT,沒有權重可下載,因此使用量以代幣計算:過去30天內透過 OpenRouter(許多應用使用的閘道)讀取和生成的文字片段。每 10,000,000 代幣算作一次下載。來源:OpenRouter (openrouter.ai/rankings),CC BY 4.0。
完整模型(檢查點)
權重本身,是能獨立生成的檔案。它會有額外加分,因為其他附加檔案都依賴它。
LoRA和嵌入
小型附加檔案,用來引導別人的權重走向某種風格、角色或概念。它們無法獨立運行。
家族與權重
模型所建立的基礎,例如SD 1.5、SDXL、Flux或Wan。每個模型都繼承其家族權重的發布日期。
年齡
根據家族權重發布時間距今多久,扣除的度數:每年150°,最多750°。它會保留那些有多年累積下載的舊模型,防止它們從排行榜頂端消失。
家族加成
針對本站目前推廣的某個家族的LoRA給予的小幅度限制加成,會在分解中顯示。
替代分數
給尚無來源報告的模型一個穩定的最低分,讓列表保持完整。它永遠不會高於有數據的模型。
全新!(寬限期)
不到 7 天的新模型會顯示「全新!」而非分數,且不列入排名。分數從第一天開始計算,但一天大的模型成長最快,若不等待,週榜首將永遠是昨天剛出的模型,而非持續一週的。
趨勢
模型在某段時間內的成長與典型模型同期成長的比較。比典型快表示上升,比典型慢表示下降。
典型模型
目錄中的中間值:一半模型在該期間成長較快,一半較慢。
這個模型的受歡迎程度跟整個目錄相比的變化:它在每個時期的下載量、喜歡數和使用量的成長,跟同一時期一般模型的成長相比,還有當時的熱度分數。高於一般成長代表上升,低於則是下降。過去的數據是從今天的總數、模型的第一天和有兩次讀數時的下載速度推算出來的;如果模型在某時期開始時不存在,會顯示 n/a。
範例作品
以下提示詞和參數由在 Civitai 上創作這些作品的人分享。選擇一張作品查看它是如何生成的。
參數
取樣器
Euler a
步數
27
引導強度
4
尺寸
768x768
Clip skip
2
使用權重
1
提示詞
potato robot assembly line, massive lego-built factory where potatoes are peeled, mashed, and shaped into mechanical bots, steam-powered mash press, conveyor belts transporting skins, red-hot gravy pipes overhead, robotic arms assembling figures with carrot bolts and pea eyes, comically industrial atmosphere, factory floor in warm tones, blend of toy-scale proportions with large mechanical logic, humorous chaos, overhead view of organized food industry madness, contrast of soft ingredients and hard structure, playful absurdity, (M.A.S.H., Lego)
負面提示詞
nudity, plastic skin, anime eyes, human characters, muscle tone, semi-realistic bodies, smooth surfaces, shiny materials, over-rendered lighting, cinematic bloom, photorealism, detailed human anatomy, provocative themes, lens flares, sweat rendering, anatomical focus, hyperreal detail
參數
取樣器
Euler a
步數
27
引導強度
4
尺寸
768x768
Clip skip
2
使用權重
1
提示詞
lego trench filled with mashed potatoes, battlefield of food toys, little potato soldiers launching butter bombs, gravy rivers flowing through craters, lego tanks with scoop wheels, clouds shaped like steam, cinematic dusk lighting, bittersweet nostalgic tone, fusion of childhood imagination and wartime parody, absurd historical reenactment, potato skins as camouflage, blocky structures crumbling into creamy rubble, toy realism, (M.A.S.H., Lego)
負面提示詞
nudity, anime proportions, plastic aesthetic, shiny skin, exaggerated anatomy, emotional expression, dramatic shading, hypersexual elements, visible muscles, digital sheen, close-up realism, hyper-detail of skin, CGI smoothness, explicit focus, filmic glow
參數
取樣器
Euler a
步數
10
引導強度
1
種子
1184656305
尺寸
512x768
Clip skip
2
提示詞
<lora:Calligraphy-ink-style-darquelilly-v1:1> calligraphyinkstyle, red color, circle shape, monk temple, top of mountain, snow, sun
負面提示詞
simultaneous,bad anatomy, low-res, (watermarks:1.2), username, paintings, sketches, (worst quality:2), (low quality:2), (normal quality:2),bad anatomy, low-res, animal tail, anime, yellow light, canvas frame, ((disfigured)), ((bad art)), ((deformed)),, wierd colors, blurry, (((duplicate))), ((morbid)), ((mutilated)), [out of frame], signature, watermarks,paintings in the background, thunder, thunderstorms
參數
取樣器
DPM++ 2M Karras
步數
20
引導強度
7
種子
455859946
尺寸
512x768
Clip skip
2
提示詞
beautiful colorful fantasy world with fairies and dragons, ((masterpiece)), ((best quality)), 8k, high texture resolution,
負面提示詞
worst quality, normal quality, low quality, blurry, blurred,jpeg artifacts,((monochrome)), ((grayscale)), error,poor effort,unsharp,bad composition, ugly from far away, ugly, lowres, signature, watermark, url, website, username, patreon username, writing, text, letters, logo, out of frame, grainy, noisy, draft,
參數
取樣器
LCM
步數
6
引導強度
1
種子
268708332
尺寸
512x768
Clip skip
2
提示詞
white saber-tooth tiger, red eyes, albino, large canines
參數
取樣器
DPM++ 2M
步數
30
引導強度
7
種子
983521761
尺寸
512x768
Clip skip
2
提示詞
((masterpiece, best quality)), illustration, graphic novel, science fiction, horror, fantasy, portrait of an alien creature, galactic night sky background, <lora:tbh295-:0.7> style of H.R. Giger, <lora:XenomorphDNA:0.9> xenomorphdna,
負面提示詞
lowres,bad anatomy,bad hands,text,error,missing fingers,extra digit,fewer digits,cropped,worst quality,low quality,normal quality,jpeg artifacts,signature,watermark,username,blurry,nsfw,
這張作品沒有分享提示詞。
參數
取樣器
Euler a
步數
15
引導強度
6.5
種子
548949743
尺寸
512x768
提示詞
Astartes, silhouette, monochrome, greyscale, BREAK <lora:epi_noiseoffset2:0.65>, <lora:more_details:0.4>,
負面提示詞
BadDream, UnrealisticDream,
本機執行
dreamshaper_8.safetensors
1.99 GB · SafeTensor · fp16 · pruned
下載由 Civitai 提供。部分建立者要求先登入 Civitai。
種子檔
dreamshaper_8.safetensors
1.99 GB · 8 · 8 個種子者 ·
CivitasBay
種子檔由種子者點對點分享;ModelTrends.ai 不托管任何檔案。請用 BitTorrent 用戶端開啟磁力連結,並將完成檔案的校驗碼與列表上的校驗碼比對。