README.md

metadata

license: other
base_model: diffusers/stable-diffusion-xl-base-1.0
tags:
  - stable-diffusion-xl
  - stable-diffusion-xl-diffusers
  - stable-diffusion
  - text-to-image
  - diffusers
  - ffai
inference: true
widget:
  - text: >-
      a dog in colorful exploding clouds, dreamlike surrealism colorful smoke
      and fire coming out of it, explosion of data fragments, exploding
      background,realistic explosion, 3d digital art
    example_title: Dogo FFusion
  - text: >-
      a sprinkled donut sitting on top of a table, colorful hyperrealism,
      everything is made of candy, hyperrealistic digital painting, covered in
      sprinkles and crumbs, vibrant colors hyper realism,colorful smoke
      explosion background
    example_title: Donut FFusion
  - text: >-
      a cup of coffee with a tree in it, surreal art, awesome great composition,
      surrealism, ice cubes in tree, colorful clouds, perfectly realistic yet
      surreal
    example_title: CoFFee FFusion
  - text: >-
      brightly colored headphones with a splash of colorful paint splash, vibing
      to music, stunning artwork, music is life, beautiful digital artwork,
      concept art, cinematic, dramatic, intricate details, dark lighting
    example_title: Headset FFusion
  - text: >-
      high-quality game character digital design, Unreal Engine, Water color
      painting, Mecha- Monstrous high quality game fantasy rpg character design,
      dark rainbow Fur Scarf, inside of a Superficial Outhouse, at Twilight,
      Overdetailed art
    example_title: Digital Fusion
language:
  - en
thumbnail: >-
  https://cdn-uploads.huggingface.co/production/uploads/6380cf05f496d57325c12194/p54u7dEP1u8en0--NMEjS.png

FFXL400 Combined LoRA Model 🚀

Welcome to the FFXL400 combined LoRA model repository on Hugging Face! This model is a culmination of extensive research, bringing together the finest LoRAs from the 400GB-LoraXL repository. Our vision was to harness the power of multiple LoRAs, meticulously analyzing and integrating a select fraction of the blocks from each.

📦 Model Highlights

• Innovative Combination: This model is a strategic integration of LoRAs, maximizing the potential of each while creating a unified powerhouse.
• Versatility: The model is available in various formats including diffusers, safetensors (both fp 16 and 32), and an optimized ONNIX FP16 version for DirectML, ensuring compatibility across AMD, Intel, Nvidia, and more.
• Advanced Research: Leveraging the latest in machine learning research, the model represents a state-of-the-art amalgamation of LoRAs, optimized for performance and accuracy.

🔍 Technical Insights

This model is a testament to the advancements in the field of AI and machine learning. It was crafted with precision, ensuring that:

• Only a small percentage of the blocks from the original LoRAs (UNet and text encoders) were utilized.
• The model is primed not just for inference but also for further training and refinement.
• It serves as a benchmark for testing and understanding the cumulative impact of multiple LoRAs when used in concert.

🎨 Usage

The FFXL400 model is designed for a multitude of applications. Whether you're delving into research, embarking on a new project, or simply experimenting, this model serves as a robust foundation. Use it to:

• Investigate the cumulative effects of merging multiple LoRAs.
• Dive deep into weighting experiments with multiple LoRAs.
• Explore the nuances and intricacies of integrated LoRAs.

📈 How to Use

The model can be easily integrated into your projects. Here's a quick guide on how to use the FFXL400 model:

1. Loading the Model:

   from transformers import AutoModel, AutoTokenizer
   
   tokenizer = AutoTokenizer.from_pretrained("FFusion/FFXL400")
   model = AutoModel.from_pretrained("FFusion/FFXL400")
   

2. Performing Inference:

   input_text = "Your input here"
   inputs = tokenizer(input_text, return_tensors='pt')
   with torch.no_grad():
       outputs = model(**inputs)
   

3. Further Training: You can also use the FFXL400 as a starting point for further training. Simply load it into your training pipeline and proceed as you would with any other model.

📚 Background

The FFXL400 is built upon the insights and data from the 400GB-LoraXL repository. Each LoRA in that collection was extracted using the Low-Rank Adaptation (LoRA) technique, providing a rich dataset for research and exploration. The FFXL400 is the pinnacle of that research, representing a harmonious blend of the best LoRAs.

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We hope the FFXL400 serves as a valuable asset in your AI journey. We encourage feedback, contributions, and insights from the community to further refine and enhance this model. Together, let's push the boundaries of what's possible!