Don't need to build xformers anymore
This commit is contained in:
Augusto de la Torre
parent
0eb5a0c0e5
commit
4d9797b4ea
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@ -30,22 +30,13 @@
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "0902e735",
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"cell_type": "markdown",
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"id": "5123d4e6-281c-4475-99fd-328f4d5df734",
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"metadata": {},
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"outputs": [],
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"source": [
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"# When running on a pod designed for Automatic 1111 \n",
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"# we need to kill the webui process to free up mem for training\n",
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"!ps x | grep -E \"(relauncher|webui)\" | grep -v \"grep\" | awk '{print $1}' | xargs kill $1\n",
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"# For best results, restart the pod after the next cell completes\n",
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"\n",
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"# check system resources, make sure your GPU actually has 24GB\n",
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"# You should see something like \"0 MB / 24576 MB\" in the middle of the printout\n",
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"# if you see 0 MB / 22000 MB pick a beefier instance...\n",
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"!grep Swap /proc/meminfo\n",
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"!swapon -s\n",
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"!nvidia-smi"
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"Here we ensure that EveryDream2trainer is installed, and we disable the Automatic 1111 web-ui. But the vram consumed by the web-ui will not be fully freed until the pod restarts. This is especially important if you are training with large batch sizes."
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]
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},
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{
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@ -58,13 +49,34 @@
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"import os\n",
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"\n",
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"%cd /workspace\n",
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"!echo pass > /workspace/stable-diffusion-webui/relauncher.py\n",
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"if not os.path.exists(\"EveryDream2trainer\"):\n",
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" !git clone https://github.com/victorchall/EveryDream2trainer\n",
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"\n",
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"%cd EveryDream2trainer\n",
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"%mkdir input\n",
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"!python utils/get_yamls.py"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "0902e735",
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"metadata": {},
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"outputs": [],
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"source": [
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"# When running on a pod designed for Automatic 1111 \n",
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"# we need to kill the webui process to free up mem for training\n",
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"!ps x | grep -E \"(relauncher|webui)\" | awk '{print $1}' | xargs kill $1\n",
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"\n",
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"# check system resources, make sure your GPU actually has 24GB\n",
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"# You should see something like \"0 MB / 24576 MB\" in the middle of the printout\n",
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"# if you see 0 MB / 22000 MB pick a beefier instance...\n",
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"!grep Swap /proc/meminfo\n",
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"!swapon -s\n",
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"!nvidia-smi"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0bf1e8cd",
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@ -102,9 +114,9 @@
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"!python -m pip install --upgrade pip\n",
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"\n",
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"!pip install requests==2.25.1\n",
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"!pip install -U -I torch==1.13.1+cu116 torchvision==0.14.1+cu116 --extra-index-url \"https://download.pytorch.org/whl/cu116\"\n",
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"!pip install -U -I torch==1.13.1+cu117 torchvision==0.14.1+cu117 --extra-index-url \"https://download.pytorch.org/whl/cu117\"\n",
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"!pip install transformers==4.25.1\n",
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"!pip install -U diffusers[torch]==0.10.2\n",
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"!pip install -U diffusers[torch]\n",
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"\n",
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"!pip install pynvml==11.4.1\n",
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"!pip install bitsandbytes==0.35.0\n",
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@ -115,20 +127,8 @@
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"!pip install wandb==0.13.6\n",
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"!pip install colorama==0.4.6\n",
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"!pip install -U triton\n",
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"!pip install -U ninja\n",
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"\n",
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"from subprocess import getoutput\n",
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"s = getoutput('nvidia-smi')\n",
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"\n",
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"if \"A100\" in s:\n",
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" print(\"Detected A100, installing stable xformers\")\n",
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" !pip install -U xformers\n",
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"else:\n",
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" # A5000/3090/4090 support requires us to build xformers ourselves for now\n",
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" print(\"Building xformers for SM86\")\n",
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" !apt-get update && apt-get install -y gcc g++\n",
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" !export TORCH_CUDA_ARCH_LIST=8.6 && pip install git+https://github.com/facebookresearch/xformers.git@48a77cc#egg=xformers\n",
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"\n",
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"!pip install --pre -U xformers\n",
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" \n",
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"print(\"DONE\")"
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]
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},
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@ -184,6 +184,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"%cd /workspace/EveryDream2trainer\n",
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"repo=\"panopstor/EveryDream\"\n",
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"ckpt_file=\"sd_v1-5_vae.ckpt\"\n",
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"\n",
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@ -230,16 +231,33 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"!python train.py --project_name \"ft_v1a_512_15e7\" \\\n",
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"--resume_ckpt \"{ckpt_name}\" \\\n",
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"%cd /workspace/EveryDream2trainer\n",
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"!python train.py --project_name \"sd1_mymodel_000\" \\\n",
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"--resume_ckpt \"sd_v1-5_vae\" \\\n",
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"--data_root \"input\" \\\n",
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"--resolution 512 \\\n",
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"--batch_size 8 \\\n",
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"--max_epochs 100 \\\n",
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"--save_every_n_epochs 50 \\\n",
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"--lr 1.8e-6 \\\n",
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"--lr_scheduler cosine \\\n",
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"--sample_steps 250 \\\n",
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"--useadam8bit \\\n",
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"--save_full_precision \\\n",
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"--shuffle_tags \\\n",
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"--amp \\\n",
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"--write_schedule\n",
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"\n",
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"!python train.py --project_name \"sd1_mymodel_100\" \\\n",
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"--resume_ckpt \"findlast\" \\\n",
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"--data_root \"input\" \\\n",
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"--resolution 512 \\\n",
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"--batch_size 4 \\\n",
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"--max_epochs 200 \\\n",
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"--save_every_n_epochs 25 \\\n",
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"--lr 1.5e-6 \\\n",
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"--max_epochs 100 \\\n",
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"--save_every_n_epochs 20 \\\n",
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"--lr 1.0e-6 \\\n",
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"--lr_scheduler constant \\\n",
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"--sample_steps 50 \\\n",
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"--sample_steps 150 \\\n",
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"--useadam8bit \\\n",
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"--save_full_precision \\\n",
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"--shuffle_tags \\\n",
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@ -247,38 +265,6 @@
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"--write_schedule"
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]
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},
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{
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"cell_type": "markdown",
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"id": "ca170883-2d18-4f34-adbb-aca5824a351b",
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"metadata": {},
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"source": [
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"## You can chain togther a tuning schedule using `--resume_ckpt findlast`"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f39291ef-bea9-471e-bbc7-7b681fa87eb3",
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"metadata": {},
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"outputs": [],
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"source": [
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"!python train.py --project_name \"ft_v1b_512_07e7\" \\\n",
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"--resume_ckpt findlast \\\n",
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"--data_root \"input\" \\\n",
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"--resolution 512 \\\n",
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"--batch_size 4 \\\n",
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"--max_epochs 50 \\\n",
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"--save_every_n_epochs 25 \\\n",
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"--lr 0.7e-6 \\\n",
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"--lr_scheduler constant \\\n",
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"--sample_steps 50 \\\n",
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"--useadam8bit \\\n",
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"--save_full_precision \\\n",
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"--shuffle_tags \\\n",
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"--amp \\\n",
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"--write_schedule\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "f24eee3d-f5df-45f3-9acc-ee0206cfe6b1",
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@ -320,8 +306,8 @@
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"!huggingface-cli lfs-enable-largefiles\n",
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"# fill in these three fields:\n",
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"hfusername = \"MyHfUser\"\n",
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"reponame = \"MyRepo\"\n",
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"ckpt_name = \"ft_v1b_512_15e7-ep200-gs02500.ckpt\"\n",
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"reponame = \"MyHfRepo\"\n",
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"ckpt_name = \"sd1_mymodel_000-ep100-gs01000.ckpt\"\n",
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"\n",
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"\n",
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"target_name = ckpt_name.replace('-','').replace('=','')\n",
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@ -348,7 +334,7 @@
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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@ -362,7 +348,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.9"
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"version": "3.6.10"
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},
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"vscode": {
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"interpreter": {
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