diff --git "a/satu_klik(fix).ipynb" "b/satu_klik(fix).ipynb"
new file mode 100644--- /dev/null
+++ "b/satu_klik(fix).ipynb"
@@ -0,0 +1,1075 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "uB4rIONAbz3F"
+ },
+ "source": [
+ "
\n",
+ "\n",
+ "`Terakhir diperbarui : 03 FEBRUARI 2024 | 14.10 WIB INDONESIA`\n",
+ "\n",
+ " \n",
+ "\n",
+ "\n",
+ "PERHATIAN \n",
+ "\n",
+ "Dikarenakan peraturan google collab yang terbaru Google Colab ToS dan Official Statement , diharapkan jangan menjalankan script jika terdapat warning sebagai berikut\n",
+ "\n",
+ "![image.png](data:image/png;base64,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)\n",
+ "\n",
+ "saya tidak bertanggung jawab apabila anda tetap menjalankan dan akun anda ditangguhkan sehingga tidak bisa menggunakan google colab dalam jangka waktu yang ditentukan google.\n",
+ "\n",
+ "\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "upiFioaJfziP"
+ },
+ "source": [
+ "# **Jangan lupa dibaca sampai bawah**\n",
+ "untuk menjalankan script ini tidak diperlukan spek tinggi karena menggunakan layanan berbasis cloud milik google. untuk kecepatan download file tergantung koneksi internet google dan juga banyaknya file yang didownload"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "VNi70r9E4nPM"
+ },
+ "source": [
+ "> **INFORMASI**: \n",
+ "\n",
+ "1. Karena adanya [Kebijakan] dan [Pernyataan Resmi][pernyataanresmi] Google Colab yang baru, sebagai pengguna google colab gratis akan dibatasi untuk penggunaan GPU dan CUDA***(komputasinya dibatasi)***\n",
+ "2. Jika akun sudah limit pemakaian google colab akun tersebut akan bisa dipakai lagi dalam waktu 24 jam kedepan.\n",
+ "(1 akun google memiliki batas 12 jam pemakiaan)\n",
+ "3. Dengan mengganti akun google yang dipakai akan mereset limit pemakaian, tetapi ada batasan jumlah pergantian penggunaan secara wajar (maksimal 3 akun, usahakan jangan lebih)\n",
+ "4. ~Google Colab Alternatife V2.1 mengambil Referensi Google Colab milik [Adiim EF] dan Milik [NoCrypt]~\n",
+ "5. Google Colab Alternatife V2.2 mengambil Referensi Google Colab milik [Linaqruf][Linaqruf]\n",
+ "\n",
+ "\n",
+ "\n",
+ "[kebijakan]: https://research.google.com/colaboratory/faq.html#limitations-and-restrictions\n",
+ "[adiim ef]: https://www.facebook.com/Adiim.EF\n",
+ "[NoCrypt]:https://github.com/NoCrypt\n",
+ "[pernyataanresmi]: https://twitter.com/thechrisperry/status/1649189902079381505\n",
+ "[Linaqruf]:https://github.com/Linaqruf\n",
+ "---\n",
+ "\n",
+ "> **PERINGATAN**: \n",
+ "\n",
+ "Jangan pernah sering mengganti akun untuk mengatasi limit pengguaan google colab, karena itu sudah termasuk dalam pelanggaran dalam [kebijakan baru][baru] (usahakan tidak menggunakan lebih dari 3 akun)\n",
+ "\n",
+ "[baru]:https://research.google.com/colaboratory/intl/id/faq.html\n",
+ "---\n",
+ "\n",
+ "\n",
+ "\n",
+ "> **NOTEBOOK COLLECTION**: \n",
+ "\n",
+ "| Koleksi Catatan | Deskripsi | Link |\n",
+ "| --- | --- | --- |\n",
+ "| [Fast_stable_diffusion_AUTOMATIC1111](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb)*Belum Stabil* | Stable Diffuson V1.5 (TheLastBen) | [![](https://img.shields.io/static/v1?message=Open%20in%20Colab&logo=googlecolab&labelColor=5c5c5c&color=0f80c1&label=%20&style=flat)](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb) | [![](https://img.shields.io/static/v1?message=Open%20in%20Colab&logo=googlecolab&labelColor=5c5c5c&color=0f80c1&label=%20&style=flat)](https://colab.research.google.com/github/Linaqruf/kohya-trainer/blob/main/kohya-LoRA-dreambooth.ipynb) |\n",
+ "| [Satu Klik Stable Diffusion](https://colab.research.google.com/drive/1LFohDgoe1U3rYwbAUFSLp1K6yM1QNG6i?usp=sharing) *Fix Update* | Stable Diffuson V1.5 | [![](https://img.shields.io/static/v1?message=Open%20in%20Colab&logo=googlecolab&labelColor=5c5c5c&color=0f80c1&label=%20&style=flat)](https://colab.research.google.com/drive/1LFohDgoe1U3rYwbAUFSLp1K6yM1QNG6i?usp=sharing) |\n",
+ "| [Membuat LoRA](https://colab.research.google.com/drive/1wo3hz402iQTb1ilz6zv6g1sotMlM-qoS?usp=sharing) **(TAHAP PERBAIKAN)** | Google Colab Membuat LoRA | [![](https://img.shields.io/static/v1?message=Open%20in%20Colab&logo=googlecolab&labelColor=5c5c5c&color=0f80c1&label=%20&style=flat)](https://colab.research.google.com/drive/1wo3hz402iQTb1ilz6zv6g1sotMlM-qoS?usp=sharing) |\n",
+ "| [Kohya LoRA Dreambooth](https://colab.research.google.com/github/Linaqruf/kohya-trainer/blob/main/kohya-LoRA-dreambooth.ipynb) *Normal* | Membuat LoRA (Linaqruf) | [![](https://img.shields.io/static/v1?message=Open%20in%20Colab&logo=googlecolab&labelColor=5c5c5c&color=0f80c1&label=%20&style=flat)](https://colab.research.google.com/github/Linaqruf/kohya-trainer/blob/main/kohya-LoRA-dreambooth.ipynb) |\n",
+ "| [Kohya LoRA Finetuner](https://colab.research.google.com/github/Linaqruf/kohya-trainer/blob/main/kohya-LoRA-finetuner.ipynb) *Normal* | Membuat LoRA 2 (Linaqruf) | [![](https://img.shields.io/static/v1?message=Open%20in%20Colab&logo=googlecolab&labelColor=5c5c5c&color=0f80c1&label=%20&style=flat)](https://colab.research.google.com/github/Linaqruf/kohya-trainer/blob/main/kohya-LoRA-finetuner.ipynb) |\n",
+ "| [Fast SD Chilloutmix](https://colab.research.google.com/drive/1Ty7uB6kZa_cfraZG-G6Rzu3B_spunJFy?usp=sharing) *Normal* | Stable Diffuson V1 | [![](https://img.shields.io/static/v1?message=Open%20in%20Colab&logo=googlecolab&labelColor=5c5c5c&color=0f80c1&label=%20&style=flat)](https://colab.research.google.com/drive/1Ty7uB6kZa_cfraZG-G6Rzu3B_spunJFy?usp=sharing) |\n",
+ "| [Fast SD Shadow Garden](https://colab.research.google.com/drive/1zfLPHL7MKvFtIBxUezF0O_SVb6yS6W6I?usp=sharing) *Normal* |Stable Diffusion V1|[![](https://img.shields.io/static/v1?message=Open%20in%20Colab&logo=googlecolab&labelColor=5c5c5c&color=0f80c1&label=%20&style=flat)](https://colab.research.google.com/drive/1zfLPHL7MKvFtIBxUezF0O_SVb6yS6W6I?usp=sharing)|\n",
+ "| [A1 Alternatif V2.1](https://colab.research.google.com/drive/1zxSTb-olxIfJeBslZL6H967_vEnzlGZi?usp=sharing) *Fix Update* | Stable Diffuson V2.1 | [![](https://img.shields.io/static/v1?message=Open%20in%20Colab&logo=googlecolab&labelColor=5c5c5c&color=0f80c1&label=%20&style=flat)](https://colab.research.google.com/drive/1zxSTb-olxIfJeBslZL6H967_vEnzlGZi?usp=sharing) |\n",
+ "| [A2 Alternatif Spesial ](https://colab.research.google.com/drive/1pTC4P17ZkFKAxNX2UVnwU0c6bn8DRWwv?usp=sharing) *Fix Update* | Stable Diffuson V2.2 | [![](https://img.shields.io/static/v1?message=Open%20in%20Colab&logo=googlecolab&labelColor=5c5c5c&color=0f80c1&label=%20&style=flat)](https://colab.research.google.com/drive/1pTC4P17ZkFKAxNX2UVnwU0c6bn8DRWwv?usp=sharing)|\n",
+ "| [Alternatif Spesial `KHUSUS SAWERIA`](https://colab.research.google.com/drive/1cRZwgt0WvJCDML4OI860fYKF2HaDW6SY?usp=sharing) *Fix Update* | Stable Diffuson V2.2 | [![](https://img.shields.io/static/v1?message=Open%20in%20Colab&logo=googlecolab&labelColor=5c5c5c&color=0f80c1&label=%20&style=flat)](https://colab.research.google.com/drive/1cRZwgt0WvJCDML4OI860fYKF2HaDW6SY?usp=sharing) |\n",
+ "| [Alternatif Spesial Satu Klik](https://colab.research.google.com/drive/1LjOYLyFgaeB2CAXVgmfkuK5mQ3XoAIRI#scrollTo=VNi70r9E4nPM) *Fix Update* | Stable Diffuson V2.2 | [![](https://img.shields.io/static/v1?message=Open%20in%20Colab&logo=googlecolab&labelColor=5c5c5c&color=0f80c1&label=%20&style=flat)](https://colab.research.google.com/drive/1LjOYLyFgaeB2CAXVgmfkuK5mQ3XoAIRI#scrollTo=VNi70r9E4nPM) |\n",
+ "|[Cagliostro-Colab-UI](https://colab.research.google.com/github/Linaqruf/sd-notebook-collection/blob/main/cagliostro-colab-ui.ipynb#scrollTo=SaAJk33ppFw1) *Has stopped updating* |Linaqruf Stable Diffusion|[![](https://img.shields.io/static/v1?message=Open%20in%20Colab&logo=googlecolab&labelColor=5c5c5c&color=0f80c1&label=%20&style=flat)](https://colab.research.google.com/github/Linaqruf/sd-notebook-collection/blob/main/cagliostro-colab-ui.ipynb#scrollTo=SaAJk33ppFw1)|\n",
+ "| [Huggingface Collection Galery](https://huggingface.co/spaces/huggingface-projects/diffusers-gallery) | Koleksi Galeri Huggingface | [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/huggingface-projects/diffusers-gallery)|\n",
+ "| [VAE Collection](https://huggingface.co/vorstcavry/vaecollection1/tree/main)| Koleksi VAE | [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/vorstcavry/vaecollection/tree/main)|\n",
+ "| [AI Voice Changer](https://huggingface.co/spaces/vorstcavry/vits-models) | AI Pengubah Suara | [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/vorstcavry/vits-models)|\n",
+ "| [AI Remove Background](https://huggingface.co/spaces/vorstcavry/anime-remove-background) | AI Penghapus Background | [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/vorstcavry/anime-remove-background)|\n",
+ "| [Stable Diffusion Extension](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Extensions) | Extension Stable Diffusion |[![Extension](https://badgen.net/badge/icon/GitHub?icon=github&label=Stable%20Diffusion)](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Extensions)|\n",
+ "\n",
+ "---"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "t5hAbVBXc8pw"
+ },
+ "source": [
+ "PERINGATAN \n",
+ "DILARANG KERAS MENYEBARKAN GAMBAR DENGAN KONTEN NSFW REALISIC KE MEDIA SOSIAL"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "fXIRZfPj1jYQ"
+ },
+ "source": [
+ "\n",
+ "\n",
+ "#***STABLE DIFFUSION SATU KLIK*** \n",
+ "\n",
+ " \n",
+ "\n",
+ "\n",
+ "\n",
+ "*Bagi yang mau support saya bisa menuju Saweria, KO-FI dan Trakteer dibawah ini*\n",
+ "\n",
+ "*For those who want to support me, you can go to Saweria, KO-FI and Trakteer below*\n",
+ "\n",
+ " \n",
+ " \n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "9L8JBzkHs0OS"
+ },
+ "source": [
+ "\n",
+ "\n",
+ "##***BAGIAN BAWAH INI HANYA AKAN BERJALAN DENGAN NORMAL JIKA MEMILIKI LANGGANAN GOOGLE COLAB PRO*** \n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 1000
+ },
+ "id": "pvvrYYcDoES_",
+ "outputId": "a6521ad1-5613-47fb-9347-3d333a02d694"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "/content\n"
+ ]
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ ""
+ ],
+ "text/html": [
+ "\n",
+ " Terima kasih Telah Menggunakan Notebook google colab StableDiffusion milik Remaja Pekalongan.
\n",
+ " "
+ ]
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ ""
+ ],
+ "text/html": [
+ " "
+ ]
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ ""
+ ],
+ "text/html": [
+ "\n",
+ " \n",
+ "
\n",
+ " Subscribe \n",
+ " \n",
+ " \n",
+ " \n",
+ "
\n",
+ " Support \n",
+ " \n",
+ " \n",
+ " \n",
+ "
\n",
+ " Saweria \n",
+ " \n",
+ " \n",
+ " \n",
+ "
\n",
+ " Discord \n",
+ " \n",
+ "
"
+ ]
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "/content\n",
+ "Tunggu sebentar...\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "100%|██████████| 3/3 [00:15<00:00, 5.28s/it]\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\u001b[0m\u001b[0;32mInstalling ubuntu dependencies\u001b[0m\n",
+ "/content/vorst-cavry\n",
+ "warning: redirecting to https://github.com/AUTOMATIC1111/stable-diffusion-webui/\n",
+ "Already up to date.\n",
+ "HEAD is now at cf2772fa Merge branch 'release_candidate'\n",
+ "Menggunakan Versi Terbaru\n",
+ "Install tunnel dan runtime script...\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "100%|██████████| 4/4 [00:01<00:00, 3.03it/s]\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Install Bahan tambahan...\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "100%|██████████| 3/3 [00:02<00:00, 1.47it/s]\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Menghapus bahan yang tidak dibutuhkan...\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "100%|██████████| 4/4 [00:00<00:00, 297.35it/s]\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "/content/vorst-cavry/extensions\n",
+ "Memasang Ekstension...\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "100%|██████████| 11/11 [00:11<00:00, 1.03s/it]\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Install controlnet...\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "100%|██████████| 5/5 [00:17<00:00, 3.51s/it]\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Install Model...\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "100%|██████████| 1/1 [00:18<00:00, 18.99s/it]\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Install Bahan tambahan...\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "100%|██████████| 1/1 [00:02<00:00, 2.10s/it]\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Cloning into '/content/vorst-cavry/extensions/ncpt_colab_timer'...\n",
+ "remote: Enumerating objects: 40, done.\u001b[K\n",
+ "remote: Counting objects: 100% (40/40), done.\u001b[K\n",
+ "remote: Compressing objects: 100% (26/26), done.\u001b[K\n",
+ "remote: Total 40 (delta 9), reused 23 (delta 5), pack-reused 0\u001b[K\n",
+ "Receiving objects: 100% (40/40), 8.85 KiB | 8.85 MiB/s, done.\n",
+ "Resolving deltas: 100% (9/9), done.\n",
+ "Cloning into '/content/vorst-cavry/static'...\n",
+ "remote: Enumerating objects: 19, done.\u001b[K\n",
+ "remote: Counting objects: 100% (19/19), done.\u001b[K\n",
+ "remote: Compressing objects: 100% (14/14), done.\u001b[K\n",
+ "remote: Total 19 (delta 1), reused 0 (delta 0), pack-reused 0\u001b[K\n",
+ "Receiving objects: 100% (19/19), 13.74 KiB | 3.43 MiB/s, done.\n",
+ "Resolving deltas: 100% (1/1), done.\n",
+ "/content/vorst-cavry\n",
+ "Python 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0]\n",
+ "Version: v1.7.0\n",
+ "Commit hash: cf2772fab0af5573da775e7437e6acdca424f26e\n",
+ "Installing clip\n",
+ "Installing open_clip\n",
+ "Cloning Stable Diffusion into /content/vorst-cavry/repositories/stable-diffusion-stability-ai...\n",
+ "Cloning into '/content/vorst-cavry/repositories/stable-diffusion-stability-ai'...\n",
+ "remote: Enumerating objects: 580, done.\u001b[K\n",
+ "remote: Counting objects: 100% (357/357), done.\u001b[K\n",
+ "remote: Compressing objects: 100% (128/128), done.\u001b[K\n",
+ "remote: Total 580 (delta 260), reused 229 (delta 229), pack-reused 223\u001b[K\n",
+ "Receiving objects: 100% (580/580), 73.44 MiB | 48.17 MiB/s, done.\n",
+ "Resolving deltas: 100% (279/279), done.\n",
+ "Cloning Stable Diffusion XL into /content/vorst-cavry/repositories/generative-models...\n",
+ "Cloning into '/content/vorst-cavry/repositories/generative-models'...\n",
+ "remote: Enumerating objects: 860, done.\u001b[K\n",
+ "remote: Counting objects: 100% (481/481), done.\u001b[K\n",
+ "remote: Compressing objects: 100% (212/212), done.\u001b[K\n",
+ "remote: Total 860 (delta 363), reused 269 (delta 269), pack-reused 379\u001b[K\n",
+ "Receiving objects: 100% (860/860), 42.67 MiB | 38.98 MiB/s, done.\n",
+ "Resolving deltas: 100% (444/444), done.\n",
+ "Cloning K-diffusion into /content/vorst-cavry/repositories/k-diffusion...\n",
+ "Cloning into '/content/vorst-cavry/repositories/k-diffusion'...\n",
+ "remote: Enumerating objects: 1340, done.\u001b[K\n",
+ "remote: Counting objects: 100% (622/622), done.\u001b[K\n",
+ "remote: Compressing objects: 100% (86/86), done.\u001b[K\n",
+ "remote: Total 1340 (delta 576), reused 547 (delta 536), pack-reused 718\u001b[K\n",
+ "Receiving objects: 100% (1340/1340), 242.04 KiB | 3.06 MiB/s, done.\n",
+ "Resolving deltas: 100% (939/939), done.\n",
+ "Cloning CodeFormer into /content/vorst-cavry/repositories/CodeFormer...\n",
+ "Cloning into '/content/vorst-cavry/repositories/CodeFormer'...\n",
+ "remote: Enumerating objects: 594, done.\u001b[K\n",
+ "remote: Counting objects: 100% (594/594), done.\u001b[K\n",
+ "remote: Compressing objects: 100% (316/316), done.\u001b[K\n",
+ "remote: Total 594 (delta 287), reused 493 (delta 269), pack-reused 0\u001b[K\n",
+ "Receiving objects: 100% (594/594), 17.31 MiB | 36.84 MiB/s, done.\n",
+ "Resolving deltas: 100% (287/287), done.\n",
+ "Cloning BLIP into /content/vorst-cavry/repositories/BLIP...\n",
+ "Cloning into '/content/vorst-cavry/repositories/BLIP'...\n",
+ "remote: Enumerating objects: 277, done.\u001b[K\n",
+ "remote: Counting objects: 100% (165/165), done.\u001b[K\n",
+ "remote: Compressing objects: 100% (30/30), done.\u001b[K\n",
+ "remote: Total 277 (delta 137), reused 136 (delta 135), pack-reused 112\u001b[K\n",
+ "Receiving objects: 100% (277/277), 7.03 MiB | 25.01 MiB/s, done.\n",
+ "Resolving deltas: 100% (152/152), done.\n",
+ "Installing requirements for CodeFormer\n",
+ "Installing requirements\n",
+ "Installing sd-webui-controlnet requirement: fvcore\n",
+ "Installing sd-webui-controlnet requirement: mediapipe\n",
+ "Installing sd-webui-controlnet requirement: onnxruntime\n",
+ "Installing sd-webui-controlnet requirement: svglib\n",
+ "ControlNet init warning: Unable to install insightface automatically. Please try run `pip install insightface` manually.\n",
+ "Installing sd-webui-controlnet requirement: handrefinerportable\n",
+ "Installing sd-webui-controlnet requirement: depth_anything\n",
+ "Installing pycloudflared\n",
+ "Launching Web UI with arguments: --listen --enable-insecure-extension-access --theme dark --no-half-vae --disable-console-progressbars --share --disable-safe-unpickle --no-hashing --opt-sdp-attention --multiple\n",
+ "2024-02-03 07:06:52.391422: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
+ "2024-02-03 07:06:52.391472: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
+ "2024-02-03 07:06:52.392789: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
+ "2024-02-03 07:06:53.633986: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
+ "no module 'xformers'. Processing without...\n",
+ "no module 'xformers'. Processing without...\n",
+ "No module 'xformers'. Proceeding without it.\n",
+ "[AddNet] Updating model hashes...\n",
+ "0it [00:00, ?it/s]\n",
+ "[AddNet] Updating model hashes...\n",
+ "0it [00:00, ?it/s]\n",
+ "ControlNet preprocessor location: /content/vorst-cavry/extensions/controlnet-s/annotator/downloads\n",
+ "2024-02-03 07:06:58,470 - ControlNet - \u001b[0;32mINFO\u001b[0m - ControlNet v1.1.440\n",
+ "2024-02-03 07:06:58,694 - ControlNet - \u001b[0;32mINFO\u001b[0m - ControlNet v1.1.440\n",
+ "Model Downloader v1.0.8\n",
+ "Checking Directories...\n",
+ "all Directories already Created.\n",
+ "Tag Autocomplete: Could not locate model-keyword extension, Lora trigger word completion will be limited to those added through the extra networks menu.\n",
+ "all detected, remote.moe trying to connect...\n",
+ "Warning: Permanently added 'localhost.run' (RSA) to the list of known hosts.\n",
+ "all detected, cloudflared trying to connect...\n",
+ "Download cloudflared...: 100% 34.8M/34.8M [00:00<00:00, 182MB/s]\n",
+ "Loading weights [None] from /content/vorst-cavry/models/Stable-diffusion/AnyLoRA_bakedVae_blessed_fp16.safetensors\n",
+ "2024-02-03 07:07:11,270 - ControlNet - \u001b[0;32mINFO\u001b[0m - ControlNet UI callback registered.\n",
+ "/content/vorst-cavry/extensions/additional-networks-s/scripts/metadata_editor.py:343: GradioDeprecationWarning: The `style` method is deprecated. Please set these arguments in the constructor instead.\n",
+ " with gr.Row().style(equal_height=False):\n",
+ "/content/vorst-cavry/extensions/additional-networks-s/scripts/metadata_editor.py:423: GradioDeprecationWarning: The `style` method is deprecated. Please set these arguments in the constructor instead.\n",
+ " cover_image = gr.Image(label=\"Cover image\", elem_id=\"additional_networks_cover_image\", source=\"upload\", interactive=can_edit, type=\"pil\", image_mode=\"RGBA\").style(height=480)\n",
+ "Creating model from config: /content/vorst-cavry/configs/v1-inference.yaml\n",
+ "/content/vorst-cavry/extensions/sd-model-downloader/scripts/model-downloader.py:310: GradioDeprecationWarning: The `style` method is deprecated. Please set these arguments in the constructor instead.\n",
+ " image.style(width=156, height=234)\n",
+ "Public WebUI Colab URL: None \n",
+ "Public WebUI Colab URL: https://35627072-87f9-45d8.gradio.live \n",
+ "Public WebUI Colab URL: https://5a24c8f582c448.lhr.life\n",
+ "vocab.json: 100% 961k/961k [00:00<00:00, 14.1MB/s]\n",
+ "merges.txt: 100% 525k/525k [00:00<00:00, 12.0MB/s]\n",
+ "special_tokens_map.json: 100% 389/389 [00:00<00:00, 2.40MB/s]\n",
+ "tokenizer_config.json: 100% 905/905 [00:00<00:00, 6.48MB/s]\n",
+ "config.json: 100% 4.52k/4.52k [00:00<00:00, 21.7MB/s]\n",
+ "Please do not use this link we are getting ERROR: Exception in ASGI application: https://48f9e9dc2363d0f1dd.gradio.live\n",
+ "Public WebUI Colab URL: https://ser-display-microwave-namely.trycloudflare.com\n",
+ "Startup time: 161.4s (prepare environment: 131.4s, import torch: 4.8s, import gradio: 1.0s, setup paths: 3.0s, initialize shared: 0.4s, other imports: 1.4s, setup codeformer: 0.2s, load scripts: 13.2s, initialize extra networks: 0.2s, create ui: 2.1s, gradio launch: 2.7s, app_started_callback: 0.8s).\n",
+ "Applying attention optimization: sdp... done.\n",
+ "Model loaded in 18.4s (load weights from disk: 2.0s, create model: 2.1s, apply weights to model: 13.0s, load textual inversion embeddings: 0.5s, calculate empty prompt: 0.6s).\n"
+ ]
+ }
+ ],
+ "source": [
+ "##Jalankan dengan sekali tekan\n",
+ "#@title ***Jalankan dengan sekali tekan*** \n",
+ "%cd /content\n",
+ "from IPython.display import HTML, display\n",
+ "\n",
+ "def display_text_box(content, width=\"485px\", height=\"30px\"):\n",
+ " html_content = f'''\n",
+ " {content}
\n",
+ " '''\n",
+ " display(HTML(html_content))\n",
+ "\n",
+ "text_content = \"Terima kasih Telah Menggunakan Notebook google colab StableDiffusion milik Remaja Pekalongan.\"\n",
+ "\n",
+ "display_text_box(text_content, width=\"485px\", height=\"30px\")\n",
+ "\n",
+ "from IPython.display import HTML, Image\n",
+ "\n",
+ "def display_image():\n",
+ " image_url = \"https://i.ibb.co/dtgPhdg/Cuplikan-layar-2023-07-30-165548.png\"\n",
+ " image_html = f' '\n",
+ "\n",
+ " display(HTML(image_html))\n",
+ "\n",
+ "display_image()\n",
+ "from IPython.display import HTML\n",
+ "\n",
+ "def create_button_with_link(label, link):\n",
+ " button_id = label.lower().replace(\" \", \"_\")\n",
+ " return f'''\n",
+ " \n",
+ " \n",
+ " {label} \n",
+ " \n",
+ " '''\n",
+ "\n",
+ "subscribe_button = create_button_with_link(\"Subscribe\", \"https://www.youtube.com/@remajapekalongan\")\n",
+ "support_button = create_button_with_link(\"Support\", \"https://ko-fi.com/vorstcavry\")\n",
+ "saweria_button = create_button_with_link(\"Saweria\", \"https://http://saweria.co/vorstcavry\")\n",
+ "discord_button = create_button_with_link(\"Discord\", \"https://discord.gg/fg9kvMqUmD\")\n",
+ "\n",
+ "buttons_html = f'{subscribe_button} {support_button} {saweria_button} {discord_button}
'\n",
+ "display(HTML(buttons_html))\n",
+ "\n",
+ "\n",
+ "import time\n",
+ "try:\n",
+ " start_colab\n",
+ "except:\n",
+ " start_colab = int(time.time())-5\n",
+ "\n",
+ "%cd /content\n",
+ "\n",
+ "#@markdown **Update** [Pilih Versi Repo]\n",
+ "import os\n",
+ "import time\n",
+ "import shutil\n",
+ "import subprocess\n",
+ "import threading\n",
+ "import sys\n",
+ "import random\n",
+ "import string\n",
+ "from google.colab.output import eval_js\n",
+ "from IPython.utils import capture\n",
+ "from tqdm import tqdm\n",
+ "\n",
+ "python_version = \".\".join(sys.version.split(\".\")[:2])\n",
+ "colablib_path = f\"/usr/local/lib/python{python_version}/dist-packages/colablib\"\n",
+ "if not os.path.exists(colablib_path):\n",
+ " subprocess.run(['pip', 'install', 'git+https://github.com/Linaqruf/colablib'])\n",
+ "\n",
+ "\n",
+ "packages = [\n",
+ " \"pip install -q gradio_client==0.2.7 -U\",\n",
+ " \"pip install insightface\",\n",
+ " \"pip install --upgrade urllib3 chardet charset_normalizer requests\",\n",
+ " \"git clone https://tinyurl.com/vorstcavry-remajapekalongan /content/vorst-cavry\"\n",
+ "]\n",
+ "for install in tqdm(packages, desc=print(\"Tunggu sebentar...\")):\n",
+ " os.system(install)\n",
+ "\n",
+ "from pydantic import BaseModel\n",
+ "from typing import List, Optional\n",
+ "from colablib.colored_print import cprint, print_line\n",
+ "from colablib.utils import py_utils, config_utils, package_utils\n",
+ "from colablib.utils import config_utils, py_utils, git_utils\n",
+ "from colablib.utils.config_utils import pastebin_reader as read\n",
+ "from colablib.utils.ubuntu_utils import ubuntu_deps\n",
+ "from colablib.sd_models.downloader import aria2_download, download, get_modelname\n",
+ "from colablib.utils.py_utils import get_filename\n",
+ "from colablib.utils.ubuntu_utils import unionfuse\n",
+ "from colablib.utils.git_utils import clone_repo\n",
+ "from colablib.utils.config_utils import read_config\n",
+ "from colablib.utils.git_utils import update_repo, batch_update, validate_repo, reset_repo, patch_repo\n",
+ "%store -r\n",
+ "\n",
+ "def pre_download(dir, urls, desc, overwrite=False):\n",
+ " gpu_info = py_utils.get_gpu_info()\n",
+ " version = py_utils.get_python_version().split()[0]\n",
+ " major_minor = \".\".join(version.split(\".\")[:2])\n",
+ " xformers_version = \"0.0.20\"\n",
+ " python_path = f\"/usr/local/lib/python{major_minor}/dist-packages/\"\n",
+ " ffmpy_path = os.path.join(python_path, \"ffmpy-0.3.0.dist-info\")\n",
+ "\n",
+ " if os.path.exists(ffmpy_path):\n",
+ " shutil.rmtree(ffmpy_path)\n",
+ "\n",
+ " subprocess.run(['pip', 'uninstall', '-y', 'xformers'], check=True)\n",
+ "\n",
+ "def install_dependencies():\n",
+ " ubuntu_deps = [\"aria2\", \"unionfs-fuse\"]\n",
+ " cprint(\"Installing ubuntu dependencies\", color=\"green\")\n",
+ " subprocess.run([\"apt\", \"install\"] + ubuntu_deps)\n",
+ "\n",
+ "install_dependencies()\n",
+ "\n",
+ "repo = \"update\" #@param [\"update\", \"standar\", \"default\"]\n",
+ "\n",
+ "\n",
+ "def git_checkout(commit_hash, folder_path):\n",
+ " os.chdir(folder_path)\n",
+ " subprocess.run(['git', 'checkout', commit_hash])\n",
+ "\n",
+ "if (repo == \"update\"):\n",
+ " %cd /content/vorst-cavry\n",
+ " !git pull\n",
+ " !git reset --hard\n",
+ " !sed -i -e 's/\\[\"sd_model_checkpoint\"\\]/\\[\"sd_model_checkpoint\",\"sd_vae\",\"CLIP_stop_at_last_layers\"\\]/g' /content/vorst-cavry/modules/shared_options.py\n",
+ " print(\"Menggunakan Versi Terbaru\")\n",
+ "elif (repo == \"standar\"):\n",
+ " %cd /content/vorst-cavry\n",
+ " folder_path = '/content/vorst-cavry'\n",
+ " commit_hash = 'baf6946e06249c5af9851c60171692c44ef633e0'\n",
+ " git_checkout(commit_hash, folder_path)\n",
+ " !sed -i -e '''/from modules import launch_utils/a\\import os''' /content/vorst-cavry/launch.py\n",
+ " !sed -i -e '''/ prepare_environment()/a\\ os.system\\(f\\\"\"\"sed -i -e ''\\\"s/dict()))/dict())).cuda()/g\\\"'' /content/vorst-cavry/repositories/stable-diffusion-stability-ai/ldm/util.py\"\"\")''' /content/vorst-cavry/launch.py\n",
+ " !sed -i -e 's/\\[\"sd_model_checkpoint\"\\]/\\[\"sd_model_checkpoint\",\"sd_vae\",\"CLIP_stop_at_last_layers\"\\]/g' /content/vorst-cavry/modules/shared.py\n",
+ " print(\"Menggunakan Versi 1.5\")\n",
+ "elif (repo == \"default\"):\n",
+ " !sed -i -e 's/\\[\"sd_model_checkpoint\"\\]/\\[\"sd_model_checkpoint\",\"sd_vae\",\"CLIP_stop_at_last_layers\"\\]/g' /content/vorst-cavry/modules/shared_options.py\n",
+ " print(\"Menggunakan Stable Diffusion 1.6\")\n",
+ "\n",
+ "import os\n",
+ "from tqdm import tqdm\n",
+ "packages = [\n",
+ " \"git clone https://github.com/vorstcavry/vorstcavry-tunnels /content/vorst-cavry/extensions/tunnels\",\n",
+ " \"aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/vorstcavry/test/resolve/main/styles.csv -d /content/vorst-cavry -o styles.csv\",\n",
+ " \"aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/embed/upscale/resolve/main/4x-UltraSharp.pth -d /content/vorst-cavry/models/ESRGAN -o 4x-UltraSharp.pth\",\n",
+ " \"wget https://raw.githubusercontent.com/vorstcavry/s-scripts/main/run_n_times.py -O /content/vorst-cavry/scripts/run_n_times.py\"\n",
+ "]\n",
+ "for install in tqdm(packages, desc=print(\"Install tunnel dan runtime script...\")):\n",
+ " os.system(install)\n",
+ "\n",
+ "import os\n",
+ "from tqdm import tqdm\n",
+ "packages = [\n",
+ " \"git clone https://github.com/vorstcavry/lora /content/vorst-cavry/models/Lora/Lora-set\",\n",
+ " \"git clone https://github.com/vorstcavry/embeddings /content/vorst-cavry/embeddings/negative\",\n",
+ " \"git clone https://github.com/vorstcavry/Checkpoint-Model /content/vorst-cavry/models/Stable-diffusion/Checkpoint-Model\"\n",
+ "]\n",
+ "for install in tqdm(packages, desc=print(\"Install Bahan tambahan...\")):\n",
+ " os.system(install)\n",
+ "\n",
+ "import os\n",
+ "from tqdm import tqdm\n",
+ "packages = [\n",
+ " \"rm -rf /content/vorst-cavry/models/Stable-diffusion/Checkpoint-Model/.git\",\n",
+ " \"rm -rf /content/vorst-cavry/embeddings/negative/.git\",\n",
+ " \"rm -rf /content/vorst-cavry/models/Lora/Lora-set/.git\",\n",
+ " \"rm -rf /content/vorst-cavry.zip\"\n",
+ "]\n",
+ "for install in tqdm(packages, desc=print(\"Menghapus bahan yang tidak dibutuhkan...\")):\n",
+ " os.system(install)\n",
+ "\n",
+ "\n",
+ "#install-ekstension\n",
+ "%cd /content/vorst-cavry/extensions\n",
+ "import os\n",
+ "from tqdm import tqdm\n",
+ "packages = [\n",
+ " \"git clone https://tinyurl.com/controlnet-s\",\n",
+ " \"git clone https://tinyurl.com/depth-lib-hand\",\n",
+ " #\"git clone https://github.com/hnmr293/posex\",\n",
+ " #\"git clone https://github.com/EdithForsaken/sd-civitai-browser-plus\"\n",
+ " \"git clone https://github.com/BlafKing/sd-civitai-browser-plus\",\n",
+ " \"git clone https://github.com/vorstcavry/images-browser\",\n",
+ " \"git clone https://github.com/Iyashinouta/sd-model-downloader\",\n",
+ " \"git clone https://github.com/IDEA-Research/DWPose\",\n",
+ " \"git clone https://tinyurl.com/additional-networks-s\",\n",
+ " \"git clone https://github.com/fkunn1326/openpose-editor\",\n",
+ " \"git clone https://tinyurl.com/openpose-edit\",\n",
+ " #\"git clone https://github.com/NoCrypt/inpaint-nav\",\n",
+ " #\"git clone https://github.com/novitalabs/sd-webui-cleaner\",\n",
+ " #\"git clone https://github.com/hnmr293/sd-webui-llul\",\n",
+ " \"git clone https://github.com/vorstcavry/tagcomplete\",\n",
+ " \"git clone https://tinyurl.com/batchlink-download\",\n",
+ " \"git clone https://tinyurl.com/aspect-ratio-v\",\n",
+ " #\"git clone https://github.com/EdithForsaken/sd-webui-cloud-inference\"\n",
+ "\n",
+ "]\n",
+ "for install in tqdm(packages, desc=print(\"Memasang Ekstension...\")):\n",
+ " os.system(install)\n",
+ "\n",
+ "#!git clone https://github.com/NoCrypt/sd_hf_out\n",
+ "\n",
+ "import os\n",
+ "from tqdm import tqdm\n",
+ "\n",
+ "packages = [\n",
+ " \"aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_canny_fp16.safetensors -d /content/vorst-cavry/models/ControlNet -o control_v11p_sd15_canny.safetensors\",\n",
+ " \"aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_inpaint_fp16.safetensors -d /content/vorst-cavry/models/ControlNet -o control_v11p_sd15_inpaint.safetensors\",\n",
+ " \"aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_lineart_fp16.safetensors -d /content/vorst-cavry/models/ControlNet -o control_v11f1p_sd15_depth.safetensors\",\n",
+ " \"aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15_openpose_fp16.safetensors -d /content/vorst-cavry/models/ControlNet -o control_v11p_sd15_openpose.safetensors\",\n",
+ " \"aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/resolve/main/control_v11p_sd15s2_lineart_anime_fp16.safetensors -d /content/vorst-cavry/models/ControlNet -o control_v11p_sd15s2_lineart_anime.safetensors\"\n",
+ "]\n",
+ "for install in tqdm(packages, desc=print(\"Install controlnet...\")):\n",
+ " os.system(install)\n",
+ "\n",
+ "\n",
+ "import os\n",
+ "from tqdm import tqdm\n",
+ "packages = [\n",
+ "\"aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/Lykon/AnyLoRA/resolve/main/AnyLoRA_bakedVae_blessed_fp16.safetensors -d /content/vorst-cavry/models/Stable-diffusion -o AnyLoRA_bakedVae_blessed_fp16.safetensors\"\n",
+ "]\n",
+ "for install in tqdm(packages, desc=print(\"Install Model...\")):\n",
+ " os.system(install)\n",
+ "\n",
+ "import os\n",
+ "from tqdm import tqdm\n",
+ "packages = [\n",
+ "\"aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt -d /content/vorst-cavry/models/VAE -o vae-ft-mse-840000-ema-pruned.ckpt\",\n",
+ "]\n",
+ "for install in tqdm(packages, desc=print(\"Install Bahan tambahan...\")):\n",
+ " os.system(install)\n",
+ "!git clone https://github.com/vorstcavry/ncpt_colab_timer /content/vorst-cavry/extensions/ncpt_colab_timer\n",
+ "!git clone https://github.com/vorstcavry/static /content/vorst-cavry/static\n",
+ "!echo -n {start_colab} > /content/vorst-cavry/static/colabTimer.txt\n",
+ "%cd /content/vorst-cavry\n",
+ "\n",
+ "\n",
+ "!python launch.py --listen --enable-insecure-extension-access --theme dark --no-half-vae --disable-console-progressbars --share --disable-safe-unpickle --no-hashing --opt-sdp-attention --multiple"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "oEk611XKY623"
+ },
+ "source": [
+ "# ***TIPS UNTUK PEMULA***: \n",
+ " \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "zJQ46qgv_s2c"
+ },
+ "source": [
+ "##***1. Positive Prompt (hal2 yang diinginkan pada gambar)***\n",
+ "Atau dalam kata lain adalah sebuah perintah atau permintaan untuk menyuruh sebuah AI di Stable Diffusion untuk menggambarkan gambar atau melakukan seuatu di stable diffuion sehingga menghasilkan karya seni yang sesuai atau hampir mendekati dengan perintah atau perintaan yang kamu berikan atau yang kamu inginkan\n",
+ "\n",
+ "![Prompt.PNG](data:image/png;base64,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)\n",
+ "\n",
+ "### **contoh sebuah prompt singkat**\n",
+ "\n",
+ "`1 girl`,\n",
+ "`looking at viewer`,\n",
+ "`smile,`,\n",
+ "`standing`,\n",
+ "`long hair`,\n",
+ "`white suit`,\n",
+ "`hair ribbon`,\n",
+ "\n",
+ "### **Jika prompt yang di atas dijadikan sebuah kalimat akan menjadi seperti ini**\n",
+ "\n",
+ "\n",
+ "artinya kamu menginginkan gambar dengan `satu orang gadis` `berrambut panjang` yang `memakai pita rambut`, `sedang melihat kearahmu`,` dengan senyuman.`\n",
+ "\n",
+ "### Prompt hanyalah sebuah detail kecil untuk menggambarkan sesuatu pada gambarmu"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "Lt6QM8kH-uY6"
+ },
+ "source": [
+ "##***2. Negative Prompt (hal2 yang tidak diinginkan pada gambar)***\n",
+ "\n",
+ "Atau dalam kata lain adalah sebuah perintah atau larangan untuk menyuruh sebuah AI di Stable Diffusion tidak menggambarkan gambar sesuaitu atau melakukan seuatu di stable diffuion yang tidak kalian inginkan dan sehingga menghasilkan karya seni yang sesuai atau hampir mendekati dengan perintah atau larangan yang kamu berikan atau yang kamu inginkan\n",
+ "\n",
+ "![Negative Prompt.PNG](data:image/png;base64,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)\n",
+ "\n",
+ "seperti contoh :\n",
+ "\n",
+ "`bad anatomy`,\n",
+ "`bad hands`,\n",
+ "`bar censor`,\n",
+ "`censored`,\n",
+ "`disconnected limbs`,\n",
+ "`extra digits`,\n",
+ "`fewer digits`,\n",
+ "`floating limbs`,\n",
+ "`low quality`,\n",
+ "`low res`,\n",
+ "`missing fingers`,\n",
+ "`missing limbs`,\n",
+ "`mutated fingers`,\n",
+ "`mutated hands`,\n",
+ "`normal quality`,\n",
+ "`out of frame`,\n",
+ "`poorly drawn`,\n",
+ "`porn`,\n",
+ "`trademark`,\n",
+ "`ugly`,\n",
+ "`watermark`,\n",
+ "`worst quality`,\n",
+ "\n",
+ "### **Jika prompt Negatif di atas di artikan dalam bahasa kita**\n",
+ "\n",
+ "\n",
+ "artinya kamu tidak menginginkan gambar yang memiliki `anatomi yang buruk`, `tangan yang buruk`, `sensor bar`, `disensor`, `anggota badan yang terputus`, `angka tambahan`, `lebih sedikit angka`, `anggota badan mengambang`, `kualitas rendah`, `resolusi rendah`, `jari-jari yang hilang`, `anggota badan yang hilang`, `jari yang bermutasi`, `tangan yang bermutasi`, `kualitas normal`, `keluar dari frame`, `digambar dengan buruk`, `pornografi`, `tanda air`, `kualitas buruk`,\n",
+ "\n",
+ "### Negatif Prompt hanyalah sebuah larangan yang diberikan oleh dirimu untuk AI agar AI tidak menggambarkan sesuatu yang tidak di inginkan pada yang akan di buat"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "nrHVl52htUR1"
+ },
+ "source": [
+ "##***3.Cara Menggunakan Additional Networks*** **Sulit digunkan untuk Pengguna HandPhone**: \n",
+ "\n",
+ "* Langkah Pertama Letakkan model LoRA yang memiliki Format seperti(*.pt, *.ckpt atau *.safetensors) di dalam folder sd-webui-additional-networks/models/LoRA.\n",
+ "\n",
+ "* Buka panel \"Additional Networks\" dari bagian kiri bawah Web UI.\n",
+ "\n",
+ "* Tekan \"Refresh models\" untuk memperbarui daftar model.\n",
+ "\n",
+ "* Pilih \"LoRA\" untuk \"Modul jaringan 1\".\n",
+ "\n",
+ "* Pilih nama file model LoRA di \"Model 1\".\n",
+ "\n",
+ "* Tetapkan bobot model (bobot negatif mungkin dapat bekerja tetapi tidak diharapkan.)\n",
+ "\n",
+ "* Ulangi untuk modul/model/bobot 2 sampai 5 jika anda memiliki model lain. Model diterapkan dalam urutan 1 sampai 5.\n",
+ "\n",
+ "* Kalian dapat menghasilkan gambar dengan model dengan jaringan tambahan ini."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "4lKK5Ab-Aiim"
+ },
+ "source": [
+ "##***4.Cara Menggunakan LoRA***\n",
+ "\n",
+ "Cara untuk mengetahui model LoRA apa saja yang dimiliki :\n",
+ "\n",
+ "![17](https://drive.google.com/uc?export=view&id=1mZKUl2hZ0n0MpKNK6cge9ovQuGYfKQc0)\n",
+ "\n",
+ "Tekan Tombol Kotak Merah yang ada lingkaran putih ini\n",
+ "\n",
+ "setelah tombol kotak kecil merah di klik akan muncul menu berikut :\n",
+ "\n",
+ "![18](https://drive.google.com/uc?export=view&id=1hpAd80k71tqS8SruYMGoSJi-nYdeGDVs)\n",
+ "\n",
+ "Tekan model LoRA untuk Menggunkannya, Kemudian model LoRA tecantum ke prompt. `Bukan yang di Negatif Prompt`\n",
+ "\n",
+ "Format nama Lora yang akan keluar :\n",
+ "\n",
+ "`1girl`, `smile`, ``\n",
+ "\n",
+ "angka 1 di belakang lora di tujukan untuk besaran lora yang akan digunakan,\n",
+ "angka 1 artinya `100%`\n",
+ "\n",
+ "Contoh\n",
+ "`0.1` = `10%`\n",
+ "`0.2` = `20%`\n",
+ "`0.3` = `30%`\n",
+ "Dan seterusnya\n",
+ "\n",
+ "jika kalian menginginkan penggunaan Dua LoRA atau lebih, kalian dapat mengurangi Skala/Rasio Loranya.\n",
+ "\n",
+ "**Contoh :**\n",
+ "\n",
+ "`1girl, smile, `\n",
+ "\n",
+ "Lora doll_japan `0.7` dan Lora doll_korea` 0.3`\n",
+ "\n",
+ "artinya adalah Lora doll_japan akan keluar sebesar `70%`dan lora doll_korea akan keluar sebesar `30%`\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "zN8PL0tl3oMI"
+ },
+ "source": [
+ "\n",
+ "##***5. Cara Mengganti Checkpoint yang dimiliki***\n",
+ "\n",
+ "tekan Model Checkpoint untuk melihat model apa saja yang dimiliki :\n",
+ "\n",
+ "![Ubah Model 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)\n",
+ "\n",
+ "Setelah itu kalian bisa memilih Model Checkpoint yang akan digunakan :\n",
+ "\n",
+ "![Ubah Model 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)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "#@title **Preview Tema :** \n",
+ "#@markdown untuk melihat preview semua tema yang bisa dipakai klik tombol [ < ] atau [ > ]\n",
+ "\n",
+ "#https://www.w3schools.com/w3css/w3css_slideshow.asp\n",
+ "import IPython\n",
+ "IPython.display.HTML(\n",
+ "\n",
+ "'''\n",
+ "\n",
+ "\n",
+ "W3.CSS \n",
+ " \n",
+ " \n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "
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+ "
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+ "
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+ "\n",
+ "
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+ "
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+ "
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+ "\n",
+ "
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+ "
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+ "
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+ "\n",
+ "
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+ "
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+ "
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+ "\n",
+ "
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+ "
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+ "
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+ "\n",
+ "
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+ "
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+ "
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+ "\n",
+ "
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+ "
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+ "
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+ "\n",
+ "
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+ "
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+ "
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+ "\n",
+ "
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+ "
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+ "
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+ "\n",
+ "\n",
+ "
❮ \n",
+ "
❯ \n",
+ "\n",
+ "
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+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "''')"
+ ],
+ "metadata": {
+ "id": "5z_kwDrRGW0w"
+ },
+ "execution_count": null,
+ "outputs": []
+ }
+ ],
+ "metadata": {
+ "accelerator": "GPU",
+ "colab": {
+ "collapsed_sections": [
+ "oEk611XKY623"
+ ],
+ "provenance": []
+ },
+ "kernelspec": {
+ "display_name": "Python 3",
+ "name": "python3"
+ },
+ "language_info": {
+ "name": "python"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
\ No newline at end of file