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You help Hailey during her workout. model - SrPoolStrange VA - 🩵KassioppiaVA🔞🤍 No Watermark available on my support site! Link in bi0! #thefirstdescendant #tFD #HaileyScott #nsfw #r34 #rule34

61,253 次观看 • 4 个月前 •via X (Twitter)

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a wholesome interaction between op and sehun 🥹🫶🏻 sehun’s message to op: “to. xinyi ❣️ i’ll definitely remember this next time. the day xinyi and sehunnie met up close for the first time” 🐥 hello~ 🤍 hello~ 🐥 *reads her name* 🤍 yes~ *says her name again* 🐥 *repeats* 🤍 eung~ i’ve liked oppa for 13 years now~ 🐥 really? (in chinese) 🤍 really! you didn’t know, right? 🐥 is this your first time coming (to the fansign)? (in chinese) 🤍 it’s my first time being this close but i’ve been to concerts and fanmeetings before~ 🐥 oh~ concerts~ (in chinese) 🤍 yes! oh, your chinese is really good~! 🐥 really~? (in chinese) 🤍 yes! 100 points! 🐥 *smiles shyly* 🤍 sehun-ah, what do you want to eat tonight? 🐥 salad! 🤍 salad? why? that’s too… 🐥 i… i can’t help it~ ㅋㅋㅋ 🤍 no, no~ ㅠㅠ you had hotpot yesterday, right? 🐥 yeah, that’s right! i had hotpot yesterday~ 🤍 hotpot again today would still be delicious! 🐥 *hesitates* 🤍 it’s okay! 🐥 it’s okay? 🤍 eung! 🐥 got it~ ㅋㅋㅋ 🤍 if we meet again next time, what would you like to say to me? what would you say? 🐥 *thinks* i’ll remember your name! 🤍 oh, really? 🐥 yes~ 🤍 *shows sehun her post-it note where she wanted him to come up with a caption for her wechat moments post about meeting him today* 🐥 oh, okay~ 🤍 let’s meet again at the concert on your birthday! 🐥 okay! sounds good~ 🤍 if we meet again, can we say hi to each other? 🐥 sure! 🤍 really? 🐥 eung (yes)! 🤍 thank you~ i love you~ 🐥 i love you too~ (in chinese) 🤍 say “i love you” too~ 🐥 yes, i love you~ (in chinese) 🤍 thank you~ i love you too~ 🐥 bba bba~ see you next time~ bba bba~ (⊼⌔⊼)👋🏻

🌸 사랑둥이 귀염둥이 세훈이 🌸

12,337 次观看 • 5 个月前

HELP mrs Nelson Joyce FIGHT BREAST CANCER. Please support and repost Her helper might be in your timeline 🙏🙏🙏 My mom NELSON JOYCE was diagnosed of breast cancer and we've been on it since the year started ,she has gone through the first stage of chemotherapy but then it didn't work effectively, now it has resulted to a wound in her breast and she's been bleeding from it . We've been buying blood to make her stable cos you know what it means loosing blood ...Going from one oncologist to the other seeking for opinion, doing one test and the other and it has taken a whole lot from us .We are going through the second stage of chemotherapy it going to cost us 4million plus ,to get the drugs, her surgery fee after the chemotherapy, also she was advised to do Radiotherapy ,we have no choice than to bring it to the public .we are here to beg you all to come to our aid financially and any other form of support you've got , your 500,1000,2000,10000,30000,50000 will go a long way in saving my mom's life .we plead with you all and we promised to be accountable and update everyone on every payment we get . For anyone in diaspora, the link to the gofundme is in the link below. and for anyone in Nigeria, the Nigerian account is FCMB NELSON RUTH AKON 5830698019 May God bless you all as you support my mom in her fight against breast cancer..Thank you For inquiries, or confirmation this is me and my sister‘s whatsapp number +2349033382306 Nelson Ruth +2349031738464 - Muyideen Peace.

Tomi the inspiring Blind man 👨‍🦯

141,196 次观看 • 1 年前

six months ago this wasn't happening on 8gb vram. running unsloth's Q4_K_XL quant of gemma 4 26b-a4b-it-qat, a sparse MoE model with only 4b active params on a single rtx 4060 laptop gpu, 8gb vram, 20+ tok/s decode. no cloud, no api, no offload hacks. just a gaming laptop on battery. what makes it fit: google's QAT (quantization aware training), plus MTP (multi token prediction) support in the latest llama.cpp builds. that combo is the single biggest unlock for local inference on low vram. rtx 3060, rtx 3070, gtx 1070, gtx 1080, rtx 4050, rtx 4060, rtx 5050, rtx 5060 — any 6-8gb consumer gpu, old or new — this model runs on it. world cup season, so i told it to build a soccer themed flappy bird clone. one shot, zero iteration, fully playable. six months ago an 8gb model could barely clone vanilla flappy bird. now it's shipping a themed game from a sparse MoE model running locally on a laptop battery. inference benchmarks: - decode throughput: 30 tok/s - context: 64k. this is the real unlock. 64k ctx is what makes a hermes agent loop viable locally on this model, not just single-turn chat. llama.cpp flags: -m gemma-4-26B-A4B-it-qat-UD-Q4_K_XL.gguf -c 64000 -cmoe --port 8080 game's deployed on my own site, built and shipped end to end with open source llm, zero closed source api dependency in the pipeline. link in the description. gguf weights on huggingface, link in the comments. pull it down, run it on whatever 8gb card is sitting in your rig. try the game and tell me your score and what you want in v2. local llms on consumer gpus stopped being a meme.

Alok

60,866 次观看 • 1 个月前