adding models

models/checkpoints/sd3.5_large.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ffef7a279d9134626e6ce0d494fba84fc1c7e720b3c7df2d19a09dc3796d8f93
+size 16460379262

provision.sh

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+#!/bin/bash
+# Ensure directories exist (relative to script location, e.g., repo root)
+mkdir -p ./models/checkpoints
+mkdir -p ./models/controlnet
+mkdir -p ./models/embeddings
+mkdir -p ./models/loras
+mkdir -p ./models/motion
+mkdir -p ./models/text_encoders
+mkdir -p ./models/upscalers
+mkdir -p ./output
+mkdir -p ./workflows
+
+# Install Hugging Face CLI if not present
+if ! command -v huggingface-cli &> /dev/null; then
+    pip install huggingface_hub
+fi
+
+# Set Hugging Face API token (via environment variable or default for testing)
+export HF_TOKEN=${HF_TOKEN:-"your_huggingface_api_token"}  # Replace or set in SimplePod env vars
+
+# Download all models from their original Hugging Face sources to your repo
+echo "Downloading models from original Hugging Face repositories..."
+# Stable Diffusion 3.5 Base (requires agreement, use token)
+huggingface-cli download --token ${HF_TOKEN} stabilityai/stable-diffusion-3.5-large sd3.5_large.safetensors --local-dir ./models/checkpoints
+
+# Dance LoRA (replace with your specific LoRA URL on Hugging Face or Civitai)
+huggingface-cli download --token ${HF_TOKEN} your-username/dance-lora dance_lora.safetensors --local-dir ./models/loras
+# If the LoRA is on Civitai, use curl/wget with the direct URL (adjust for authentication if needed):
+# curl -L -o ./models/loras/dance_lora.safetensors "https://civitai.com/api/download/<lora-id>"
+
+# AnimateDiff for Motion
+huggingface-cli download --token ${HF_TOKEN} guoyww/animatediff mm_sd_v15_v2.ckpt --local-dir ./models/motion
+
+# VAE (optional, for better quality)
+huggingface-cli download --token ${HF_TOKEN} stabilityai/sd-vae-ft-mse-original vae-ft-mse-840000-ema-pruned.safetensors --local-dir ./models/vae
+
+# ControlNet Models (optional, for pose/motion)
+huggingface-cli download --token ${HF_TOKEN} lllyasviel/ControlNet-v1-1 control_v11p_sd15_openpose.pth --local-dir ./models/controlnet
+huggingface-cli download --token ${HF_TOKEN} lllyasviel/ControlNet-v1-1 control_v11p_sd15_canny.pth --local-dir ./models/controlnet
+
+# Install ComfyUI custom nodes for SD 3.5 and motion (if needed)
+echo "Installing ComfyUI custom nodes for SD 3.5 and motion..."
+pip install git+https://github.com/civitai/sd3-comfyui.git
+git clone https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite.git ./models/ComfyUI/custom_nodes/ComfyUI-VideoHelperSuite
+
+# Ensure Rclone is installed (likely pre-installed in ai-dock/comfyui)
+if ! command -v rclone &> /dev/null; then
+    curl https://rclone.org/install.sh | sudo bash
+fi
+
+# Sync outputs from R2 on startup (optional, can be run later)
+rclone copy r2bucket:output ./output --create-empty-src-dirs
+
+# Start background sync loop for outputs to R2
+nohup bash -c "while true; do rclone sync ./output r2bucket:output; sleep 3600; done" &
+
+# Note: ComfyUI launch is not run locally; this is for SimplePod deployment
+echo "Models and structure ready for ComfyUI deployment. Push to Hugging Face and use in SimplePod."

provision_gpu.sh

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+#!/bin/bash
+# Ensure directories exist (relative to script location, e.g., repo root)
+mkdir -p ./models/checkpoints
+mkdir -p ./models/controlnet
+mkdir -p ./models/embeddings
+mkdir -p ./models/loras
+mkdir -p ./models/motion
+mkdir -p ./models/text_encoders
+mkdir -p ./models/upscalers
+mkdir -p ./output
+mkdir -p ./workflows
+
+# Install Hugging Face CLI if not present
+if ! command -v huggingface-cli &> /dev/null; then
+    pip install huggingface_hub
+fi
+
+# Set Hugging Face API token (via environment variable or default for testing)
+export HF_TOKEN=${HF_TOKEN:-"your_huggingface_api_token"}  # Replace or set in SimplePod env vars
+
+# Download all models from your Hugging Face repo
+echo "Downloading models from your Hugging Face repository..."
+huggingface-cli download --token ${HF_TOKEN} myusername/comfyui-dance-models models/checkpoints/sd3.5-base.safetensors --local-dir ./models/checkpoints
+huggingface-cli download --token ${HF_TOKEN} myusername/comfyui-dance-models models/loras/dance_lora.safetensors --local-dir ./models/loras
+huggingface-cli download --token ${HF_TOKEN} myusername/comfyui-dance-models models/motion/mm_sd_v15_v2.ckpt --local-dir ./models/motion
+huggingface-cli download --token ${HF_TOKEN} myusername/comfyui-dance-models models/vae/vae-ft-mse-840000-ema-pruned.safetensors --local-dir ./models/vae
+huggingface-cli download --token ${HF_TOKEN} myusername/comfyui-dance-models models/controlnet/control_v11p_sd15_openpose.pth --local-dir ./models/controlnet
+huggingface-cli download --token ${HF_TOKEN} myusername/comfyui-dance-models models/controlnet/control_v11p_sd15_canny.pth --local-dir ./models/controlnet
+
+# Install ComfyUI custom nodes for SD 3.5 and motion (if needed)
+echo "Installing ComfyUI custom nodes for SD 3.5 and motion..."
+pip install git+https://github.com/civitai/sd3-comfyui.git
+git clone https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite.git ./models/ComfyUI/custom_nodes/ComfyUI-VideoHelperSuite
+
+# Ensure Rclone is installed (likely pre-installed in ai-dock/comfyui)
+if ! command -v rclone &> /dev/null; then
+    curl https://rclone.org/install.sh | sudo bash
+fi
+
+# Sync outputs from R2 on startup (optional, can be run later)
+rclone copy r2bucket:output ./output --create-empty-src-dirs
+
+# Start background sync loop for outputs to R2
+nohup bash -c "while true; do rclone sync ./output r2bucket:output; sleep 3600; done" &
+
+# Note: ComfyUI launch is not run locally; this is for SimplePod deployment
+echo "Models and structure ready for ComfyUI deployment. Push to Hugging Face and use in SimplePod."