tiny cleanup to colab notebook
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{
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{
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"cells": [
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"cells": [
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{
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{
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"attachments": {},
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"cell_type": "markdown",
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"cell_type": "markdown",
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"metadata": {
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"metadata": {
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"id": "view-in-github",
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"colab_type": "text",
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"colab_type": "text"
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"id": "view-in-github"
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},
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},
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"source": [
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"source": [
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"<a href=\"https://colab.research.google.com/github/nawnie/EveryDream2trainer/blob/main/Train_Colab.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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"<a href=\"https://colab.research.google.com/github/nawnie/EveryDream2trainer/blob/main/Train_Colab.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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]
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]
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},
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},
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{
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{
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"attachments": {},
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"cell_type": "markdown",
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"cell_type": "markdown",
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"metadata": {
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"metadata": {
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"id": "blaLMSbkPHhG"
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"id": "blaLMSbkPHhG"
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@ -200,8 +202,8 @@
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": null,
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"execution_count": null,
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"metadata": {
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"metadata": {
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"id": "unaffeqGP_0A",
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"cellView": "form",
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"cellView": "form"
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"id": "unaffeqGP_0A"
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},
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},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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@ -284,6 +286,7 @@
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]
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]
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},
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},
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{
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{
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"attachments": {},
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"cell_type": "markdown",
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"cell_type": "markdown",
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"metadata": {
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"metadata": {
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"id": "EHyFzKWXX9kB"
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"id": "EHyFzKWXX9kB"
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@ -300,8 +303,8 @@
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": null,
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"execution_count": null,
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"metadata": {
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"metadata": {
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"id": "j9pEI69WXS9w",
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"cellView": "form",
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"cellView": "form"
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"id": "j9pEI69WXS9w"
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},
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},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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@ -318,9 +321,9 @@
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"%cd /content/EveryDream2trainer\n",
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"%cd /content/EveryDream2trainer\n",
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"#@markdown If you want to use a .json config or upload your own, skip this cell and run the cell below instead\n",
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"#@markdown If you want to use a .json config or upload your own, skip this cell and run the cell below instead\n",
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"!rm -r /content/EveryDream2trainer/Training_Data\n",
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"!rm -r /content/EveryDream2trainer/Training_Data\n",
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"#@markdown * Save logs and output ckpts to Gdrive (strongly suggested)\n",
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"#@markdown * Save logs and output ckpts to Gdrive (strongly suggested, will need space)\n",
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"Save_to_Gdrive = True #@param{type:\"boolean\"}\n",
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"Save_to_Gdrive = True #@param{type:\"boolean\"}\n",
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"#@markdown * Save extra data to help continue training with\n",
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"#@markdown * Save extra state information to help continue training (if you will resume later, requires high RAM shape)\n",
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"Save_optimizer_state = False #@param{type:\"boolean\"}\n",
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"Save_optimizer_state = False #@param{type:\"boolean\"}\n",
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"#@markdown * Disconnect after training to save Credits \n",
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"#@markdown * Disconnect after training to save Credits \n",
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"Disconnect_after_training = False #@param{type:\"boolean\"}\n",
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"Disconnect_after_training = False #@param{type:\"boolean\"}\n",
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@ -348,8 +351,8 @@
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"Text_lr = 5e-7 #@param {type:\"number\"}\n",
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"Text_lr = 5e-7 #@param {type:\"number\"}\n",
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"#@markdown * A learning rate scheduler can change your learning rate as training progresses.\n",
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"#@markdown * A learning rate scheduler can change your learning rate as training progresses.\n",
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"#@markdown * I recommend sticking with constant until you are comfortable with general training. \n",
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"#@markdown * I recommend sticking with constant until you are comfortable with general training. \n",
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"Schedule = \"linear\" #@param [\"constant\", \"polynomial\", \"linear\", \"cosine\"] {allow-input: true}\n",
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"Schedule = \"constant\" #@param [\"constant\", \"polynomial\", \"linear\", \"cosine\"] {allow-input: true}\n",
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"Text_lr_scheduler = \"linear\" #@param [\"constant\", \"polynomial\", \"linear\", \"cosine\"] {allow-input: true}\n",
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"Text_lr_scheduler = \"cosine\" #@param [\"constant\", \"polynomial\", \"linear\", \"cosine\"] {allow-input: true}\n",
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"#@markdown * warm up steps are useful for validation and cosine lrs\n",
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"#@markdown * warm up steps are useful for validation and cosine lrs\n",
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"lr_warmup_steps = 0 #@param{type:\"integer\"}\n",
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"lr_warmup_steps = 0 #@param{type:\"integer\"}\n",
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"lr_decay_steps = 0 #@param {type:\"number\"} \n",
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"lr_decay_steps = 0 #@param {type:\"number\"} \n",
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@ -614,6 +617,7 @@
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]
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]
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},
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},
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{
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{
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"attachments": {},
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"cell_type": "markdown",
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"cell_type": "markdown",
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"metadata": {
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"metadata": {
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"id": "fzXLJVC6OCeP"
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"id": "fzXLJVC6OCeP"
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@ -691,21 +695,22 @@
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]
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]
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},
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},
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{
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{
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"attachments": {},
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"cell_type": "markdown",
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"cell_type": "markdown",
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"source": [
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"Need some tools to Manage your large datasets check out https://github.com/victorchall/EveryDream for some usefull tools and captioner"
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],
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"metadata": {
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"metadata": {
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"id": "ls6mX94trxZV"
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"id": "ls6mX94trxZV"
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}
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},
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"source": [
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"Need some tools to Manage your large datasets check out https://github.com/victorchall/EveryDream for some usefull tools and captioner"
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]
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}
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}
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],
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],
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"metadata": {
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"metadata": {
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"accelerator": "GPU",
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"accelerator": "GPU",
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"colab": {
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"colab": {
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"provenance": [],
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"gpuType": "T4",
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"gpuType": "T4",
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"include_colab_link": true
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"include_colab_link": true,
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"provenance": []
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},
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},
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"kernelspec": {
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"kernelspec": {
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"display_name": "Python 3",
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"display_name": "Python 3",
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