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👑MODEL'S ENGAGEMENT THREAD👑 👣Theme: Foot Fetish Friday - Any feet content!👣 Featured 👑 AnasFeet 👈🏻FOLLOW! 👉🏻Repost to participate, I will retweet back the best entries and pick 1 or 2 participating model/s to FEATURE next thread! 🦄
12,317 просмотров • 2 лет назад •via X (Twitter)
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💎MODEL'S ENGAGEMENT THREAD💎 👣Theme: Toesday!👣 Featured: 3Flowers - FOLLOW! 👉🏻Repost to participate, I will retweet back the best entries and pick 1 or 2 participating model/s to FEATURE next thread! 🦄
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💎VIPFEET MODEL'S ENGAGEMENT THREAD💎 👣Theme: Toesday👣 Ladies please post your toes closeup pic/vid! 🎖️To participate Repost + Like this post, I will retweet back the best entries and pick one or two best entries for the next thread! Sunday's best entry: @Lady_Mylani ❤️🏆
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👣SEXY FOOTWEAR THURSDAY👣 🌟MODELS ENGAGEMENT THREAD🌟 All models post your sexy footwear! I will retweet🔄& FEATURE models (in future threads) WHO participate + Like♥️ & RT🔄this POST! Featured models: 👑💋 Reyna Lorenaaa Goddess Melanie scarlett SugarTootsies Footish Queen Galina
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👣FLIP FLOPS FRIDAY👣 🌟MODELS ENGAGEMENT THREAD🌟 ➕ALL models please post your feet wearing flip flops! I will retweet🔄& FEATURE models (in future threads) WHO post a flip flop picture & Like ♥️ & retweet🔄THIS tweet! Featured model: 𝗚𝗶𝗮𝗻𝗻𝗮 💕✨جلالة الملكة
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👣CLASSY FEET FRIDAY👣 🌟MODELS ENGAGEMENT THREAD🌟 Models please post your classy feet picture either in high heels or sexy sandals! For max. exposure, I will retweet the ones who have posted their classy feet + liked & RT this post! Stunning soles and toes by: @MistressCathie
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Foot Fetish Friday Ft. Mia Lake Sweetfeetsy | Mia Lake 🤤👣❤️ Go follow midnyghtdesires00 for more feet content‼️‼️‼️ Make sure to check out Mia Lake Sweetfeetsy | Mia Lake onlyfans linked in her bio🤫 Comment below🔽🔽🔽 #ig #x #tiktok #influencer #sex #model #footfetish #footworship #footlover #footmodels #mialakex #sweetfeetsy #onlyfans #of #soles #toes #goddess #findom #latina #prettyfeet #content #follow #like #repost #comment
midnyghtdesires00
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🚨🚨SILVER GIVEAWAY TIME🚨🚨 It is time to do another silver giveaway! Woohoo!! This is your chance to win another piece of silver jewlery made from the one and only JesterJum so here we go with giveaway #2 😃 Huge congrats to our last winner Supersonic Redhead🛫! She can attest to the quality of the pieces I make! This is a solid 925 silver, one of a kind wolf ring inspired by House Stark from Game of Thrones. This giveaway will last for 5 days, so the winner will be randomly chosen and announced next week on 4/16 @ 9pm CST To enter for a chance to win, you must: 1) Follow Jum 2) Like this post 3) Repost this post 4) Leave a comment (any comment you like) Each individual is only allowed 1 entry so multiple comments will not give you multiple entries. Multiple accounts per person will be disqualified — play fair! Entries from duplicate or spam accounts won't count. At the end of the week, all eligible individuals will be put into Grok and Grok will choose a random winner! This is a chance to get a 100% FREE silver ring, and with silver at an all time high, you don't want to miss this chance! **This giveaway is in no way sponsored, endorsed, or administered by X
Jum
48,162 просмотров • 3 месяцев назад
![Batch Normalization by hand ✍️ ~ 7 steps walkthrough below Batch normalization is common practice for improving training and achieving faster convergence. It sounds simple. But it is often misunderstood. 🤔 Does batch normalization involve trainable parameters, tunable hyper-parameters, or both? 🤔 Is batch normalization applied to inputs, features, weights, biases, or outputs? 🤔 How is batch normalization different from layer normalization? So I drew and calculated one entirely by hand. Goal: normalize a mini-batch of 4 examples to mean 0 and variance 1, then let the network scale it back. = 1. Given = A mini-batch of 4 training examples, each with 3 features. = 2. Linear layer = Let us multiply by the weights and add the biases. Batch norm sits after this, which answers the second question: what gets normalized is features, not inputs, weights or biases. = 3. ReLU = We apply the activation, and -2 becomes 0. Negative values are suppressed before any statistic is taken. = 4. Batch statistics = Let us compute the sum, mean, variance and standard deviation, one row at a time. A row is a feature and the four columns are the four examples, so every number here measures one feature against the rest of the batch. That is the "batch" in batch normalization, and it is exactly what layer normalization does not do. The statistics are rounded to whole numbers, which is what keeps the rest of the page doable in pen. = 5. Shift to mean 0 = We subtract the mean, in green. The four values in each feature now average to zero. = 6. Scale to variance 1 = Let us divide by the standard deviation, in orange. Each feature now has variance one, whatever scale it arrived at. = 7. Scale and shift = We multiply by a linear transformation and pass the result on. The diagonal and the last column are trainable, so having just forced every feature to mean 0 and variance 1, we hand the network the means to undo it. The outputs: Mean of each feature = [2, 1, 2] Std dev of each feature = [1, 1, 2] To the next layer = [2, -2, 2, 0], [-3, 3, 6, -3], [2, 0, 1, 2] The answers: 🤔 Both. The scale and shift are trainable, the statistics are not. Epsilon and the momentum on the running statistics are the hyper-parameters, and one mini-batch by hand needs neither. 🤔 Features, after the linear layer, not inputs, weights or biases. 🤔 Batch norm measures across the batch, one feature at a time. Layer norm measures across the features, one example at a time. 💾 Save this post!](https://image.24vids.com/tw-2079570896423911664/ext_tw_video_thumb/2079570876530298880/pu/img/w_TJ6G4bD69KBKuz.jpg)
![[Seeking VTuber for Cover Art🎨] I’ll be exhibiting at a creator event in Japan this July, so I’m looking for a VTuber to be drawn for the brochure and fabric banner. 📥 How to Apply ﹂1. Follow + RT + Like this post ﹂2. Reply to this post with your reference sheet 📌 Eligibility: VTuber 📍 Usage ・The art will be used at Creators Expo, held at Tokyo Big Sight from July 2 to 4. ・It will be featured on a booth fabric banner, brochure for visitors, the Creators Expo website, and my social media. ・Also, it may be used on my business cards, plastic folders for distribution, and other events. 🏆 Winner: 1 person ⏳ Deadline: February 28, 2025 ・The winner will be contacted in March, and the art will be completed by May. 🎨 About the Art ・Bust-up or half-body, gifted for free! ・Bright & energetic style ・Skeb-style: No requests or revisions ・Smiling expression, looking at the viewer, with VTuber-related items ・Commercial rights not included. For merchandise use, please contact me after receiving the art ＿＿＿＿＿＿＿＿＿＿＿＿ That's all. At first, I was thinking of drawing my model for the cover, but I really wanted to draw an active VTuber, so I decided to open applications. Looking forward to your entries!😊🧡 #ENVtubers](https://image.24vids.com/tw-1889111309352145107/ext_tw_video_thumb/1889102337899474944/pu/img/V2jcdiQyRltWmaoZ.jpg)
