Upload folder using huggingface_hub

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
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 *tfevents* filter=lfs diff=lfs merge=lfs -text
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+docs/kisekaeichi_result.png filter=lfs diff=lfs merge=lfs -text
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.gitignore

@@ -0,0 +1,5 @@
+__pycache__/
+.venv
+venv/
+logs/
+uv.lock

.ipynb_checkpoints/README-checkpoint.md

@@ -0,0 +1,127 @@
+# Anime Light Landscape Text-to-Video Generation
+
+This repository contains the necessary steps and scripts to generate anime-style videos using the Anime_Landscape text-to-video model with LoRA (Low-Rank Adaptation) weights. The model produces anime-style videos based on textual prompts with distinctive geometric and neon aesthetic.
+
+## Prerequisites
+
+Before proceeding, ensure that you have the following installed on your system:
+
+• **Ubuntu** (or a compatible Linux distribution)
+• **Python 3.x**
+• **pip** (Python package manager)
+• **Git**
+• **Git LFS** (Git Large File Storage)
+• **FFmpeg**
+
+## Installation
+
+1. **Update and Install Dependencies**
+
+   ```bash
+   sudo apt-get update && sudo apt-get install cbm git-lfs ffmpeg
+   ```
+
+2. **Clone the Repository**
+
+   ```bash
+   git clone https://huggingface.co/svjack/Anime_Bright_Landscape_wan_2_1_14_B_text2video_lora
+   cd Anime_Bright_Landscape_wan_2_1_14_B_text2video_lora
+   ```
+
+3. **Install Python Dependencies**
+
+   ```bash
+   pip install torch torchvision
+   pip install -r requirements.txt
+   pip install ascii-magic matplotlib tensorboard huggingface_hub datasets
+   pip install moviepy==1.0.3
+   pip install sageattention==1.0.6
+   ```
+
+4. **Download Model Weights**
+
+   ```bash
+   wget https://huggingface.co/Wan-AI/Wan2.1-T2V-14B/resolve/main/models_t5_umt5-xxl-enc-bf16.pth
+   wget https://huggingface.co/DeepBeepMeep/Wan2.1/resolve/main/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+   wget https://huggingface.co/Wan-AI/Wan2.1-T2V-14B/resolve/main/Wan2.1_VAE.pth
+   wget https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_t2v_1.3B_bf16.safetensors
+   wget https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_t2v_14B_bf16.safetensors
+   ```
+
+## Usage
+
+To generate a video, use the `wan_generate_video.py` script with the appropriate parameters. 
+
+#### Interactive Mode
+For experimenting with different prompts:
+```bash
+python wan_generate_video.py --fp8 --task t2v-14B --video_size 480 832 --video_length 81 --infer_steps 35 \
+--save_path save --output_type both \
+--dit wan2.1_t2v_14B_bf16.safetensors --vae Wan2.1_VAE.pth \
+--t5 models_t5_umt5-xxl-enc-bf16.pth \
+--attn_mode torch \
+--lora_weight ani_bright_landscape_w14_outputs/ani_bright_landscape_w14_lora-step00005500.safetensors \
+--lora_multiplier 1.0 \
+--interactive
+```
+
+```prompt
+```
+
+```prompt
+```
+
+```prompt
+```
+
+```prompt
+```
+
+```prompt
+```
+
+
+
+## Key Parameters
+
+* `--fp8`: Enable FP8 precision (recommended)
+* `--task`: Model version (`t2v-1.3B`)
+* `--video_size`: Output resolution (e.g., `480 832`)
+* `--video_length`: Number of frames (typically 81)
+* `--infer_steps`: Quality vs speed trade-off (35-50)
+* `--lora_weight`: Path to Kinich LoRA weights
+* `--lora_multiplier`: Strength of LoRA effect (1.0 recommended)
+* `--prompt`: Should include "In the style of Kinich" for best results
+
+## Style Characteristics
+
+For optimal results, prompts should describe:
+- Characters with geometric neon hair patterns
+- Black outfits with gold/teal designs
+- Futuristic or high-energy backgrounds
+- Vibrant color palettes with glowing elements
+- Dynamic poses and expressions
+
+## Output
+
+Generated videos and frames will be saved in the specified `save_path` directory with:
+- MP4 video file
+- Individual frames as PNG images
+
+## Troubleshooting
+
+• Verify all model weights are correctly downloaded
+• Ensure sufficient GPU memory (>=12GB recommended)
+• Check for version conflicts in Python packages
+
+## License
+
+This project is licensed under the MIT License.
+
+## Acknowledgments
+
+• **Hugging Face** for model hosting
+• **Wan-AI** for base models
+• **svjack** for LoRA adaptation
+
+For support, please open an issue in the repository.

.ipynb_checkpoints/Untitled-checkpoint.ipynb

@@ -0,0 +1,42 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a0d2adc9-e517-4906-b730-3fbc16a1a7e5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "python wan_generate_video.py --fp8 --task t2v-1.3B --video_size 480 832 --video_length 81 --infer_steps 35 \\\n",
+    "--save_path save --output_type both \\\n",
+    "--dit aniWan2114BFp8E4m3fn_t2v13B.safetensors --vae Wan2.1_VAE.pth \\\n",
+    "--t5 models_t5_umt5-xxl-enc-bf16.pth \\\n",
+    "--attn_mode torch \\\n",
+    "--lora_weight Kinich_w1_3_outputs/Kinich_w1_3_lora-000070.safetensors \\\n",
+    "--lora_multiplier 1.0 \\\n",
+    "--interactive\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "wan2gp",
+   "language": "python",
+   "name": "wan2gp"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

.python-version

@@ -0,0 +1 @@
+3.10

README.md

@@ -0,0 +1,127 @@
+# Anime Light Landscape Text-to-Video Generation
+
+This repository contains the necessary steps and scripts to generate anime-style videos using the Anime_Landscape text-to-video model with LoRA (Low-Rank Adaptation) weights. The model produces anime-style videos based on textual prompts with distinctive geometric and neon aesthetic.
+
+## Prerequisites
+
+Before proceeding, ensure that you have the following installed on your system:
+
+• **Ubuntu** (or a compatible Linux distribution)
+• **Python 3.x**
+• **pip** (Python package manager)
+• **Git**
+• **Git LFS** (Git Large File Storage)
+• **FFmpeg**
+
+## Installation
+
+1. **Update and Install Dependencies**
+
+   ```bash
+   sudo apt-get update && sudo apt-get install cbm git-lfs ffmpeg
+   ```
+
+2. **Clone the Repository**
+
+   ```bash
+   git clone https://huggingface.co/svjack/Anime_Bright_Landscape_wan_2_1_14_B_text2video_lora
+   cd Anime_Bright_Landscape_wan_2_1_14_B_text2video_lora
+   ```
+
+3. **Install Python Dependencies**
+
+   ```bash
+   pip install torch torchvision
+   pip install -r requirements.txt
+   pip install ascii-magic matplotlib tensorboard huggingface_hub datasets
+   pip install moviepy==1.0.3
+   pip install sageattention==1.0.6
+   ```
+
+4. **Download Model Weights**
+
+   ```bash
+   wget https://huggingface.co/Wan-AI/Wan2.1-T2V-14B/resolve/main/models_t5_umt5-xxl-enc-bf16.pth
+   wget https://huggingface.co/DeepBeepMeep/Wan2.1/resolve/main/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
+   wget https://huggingface.co/Wan-AI/Wan2.1-T2V-14B/resolve/main/Wan2.1_VAE.pth
+   wget https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_t2v_1.3B_bf16.safetensors
+   wget https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_t2v_14B_bf16.safetensors
+   ```
+
+## Usage
+
+To generate a video, use the `wan_generate_video.py` script with the appropriate parameters. 
+
+#### Interactive Mode
+For experimenting with different prompts:
+```bash
+python wan_generate_video.py --fp8 --task t2v-14B --video_size 480 832 --video_length 81 --infer_steps 35 \
+--save_path save --output_type both \
+--dit wan2.1_t2v_14B_bf16.safetensors --vae Wan2.1_VAE.pth \
+--t5 models_t5_umt5-xxl-enc-bf16.pth \
+--attn_mode torch \
+--lora_weight ani_bright_landscape_w14_outputs/ani_bright_landscape_w14_lora-step00005500.safetensors \
+--lora_multiplier 1.0 \
+--interactive
+```
+
+```prompt
+```
+
+```prompt
+```
+
+```prompt
+```
+
+```prompt
+```
+
+```prompt
+```
+
+
+
+## Key Parameters
+
+* `--fp8`: Enable FP8 precision (recommended)
+* `--task`: Model version (`t2v-1.3B`)
+* `--video_size`: Output resolution (e.g., `480 832`)
+* `--video_length`: Number of frames (typically 81)
+* `--infer_steps`: Quality vs speed trade-off (35-50)
+* `--lora_weight`: Path to Kinich LoRA weights
+* `--lora_multiplier`: Strength of LoRA effect (1.0 recommended)
+* `--prompt`: Should include "In the style of Kinich" for best results
+
+## Style Characteristics
+
+For optimal results, prompts should describe:
+- Characters with geometric neon hair patterns
+- Black outfits with gold/teal designs
+- Futuristic or high-energy backgrounds
+- Vibrant color palettes with glowing elements
+- Dynamic poses and expressions
+
+## Output
+
+Generated videos and frames will be saved in the specified `save_path` directory with:
+- MP4 video file
+- Individual frames as PNG images
+
+## Troubleshooting
+
+• Verify all model weights are correctly downloaded
+• Ensure sufficient GPU memory (>=12GB recommended)
+• Check for version conflicts in Python packages
+
+## License
+
+This project is licensed under the MIT License.
+
+## Acknowledgments
+
+• **Hugging Face** for model hosting
+• **Wan-AI** for base models
+• **svjack** for LoRA adaptation
+
+For support, please open an issue in the repository.

Untitled.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a0d2adc9-e517-4906-b730-3fbc16a1a7e5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "python wan_generate_video.py --fp8 --task t2v-1.3B --video_size 480 832 --video_length 81 --infer_steps 35 \\\n",
+    "--save_path save --output_type both \\\n",
+    "--dit aniWan2114BFp8E4m3fn_t2v13B.safetensors --vae Wan2.1_VAE.pth \\\n",
+    "--t5 models_t5_umt5-xxl-enc-bf16.pth \\\n",
+    "--attn_mode torch \\\n",
+    "--lora_weight Kinich_w1_3_outputs/Kinich_w1_3_lora-000070.safetensors \\\n",
+    "--lora_multiplier 1.0 \\\n",
+    "--interactive\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "wan2gp",
+   "language": "python",
+   "name": "wan2gp"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

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