FFXL400 Combined LoRA Model π
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.
π¦ 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.
π 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.
π¨ 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.
β οΈ License & Usage Disclaimers
Please review the full license agreement before accessing or using the models.
π΄ The models and weights available in this repository are strictly for research and testing purposes, with exceptions noted below. They are not generally intended for commercial use and are dependent on each individual LORA.
π΅ Exception for Commercial Use: The FFusionXL-BASE, FFusion-BaSE, di.FFUSION.ai-v2.1-768-BaSE-alpha, and di.ffusion.ai.Beta512 models are trained by FFusion AI using images for which we hold licenses. Users are advised to primarily use these models for a safer experience. These particular models are allowed for commercial use.
π΄ Disclaimer: FFusion AI, in conjunction with Source Code Bulgaria Ltd and BlackswanTechnologies, does not endorse or guarantee the content produced by the weights in each LORA. There's potential for generating NSFW or offensive content. Collectively, we expressly disclaim responsibility for the outcomes and content produced by these weights.
π΄ Acknowledgement: The FFusionXL-BASE model model is a uniquely developed version by FFusion AI. Rights to this and associated modifications belong to FFusion AI and Source Code Bulgaria Ltd. Ensure adherence to both this license and any conditions set by Stability AI Ltd for referenced models.
π How to Use
The model can be easily integrated into your projects. Here's a quick guide on how to use the FFXL400 model:
Loading the Model:
from transformers import AutoModel, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("FFusion/FFXL400") model = AutoModel.from_pretrained("FFusion/FFXL400")
Performing Inference:
input_text = "Your input here" inputs = tokenizer(input_text, return_tensors='pt') with torch.no_grad(): outputs = model(**inputs)
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.
π 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.
Library of Available LoRA Models π
You can choose any of the models from our repository on Hugging Face or the upcoming repository on CivitAI. Here's a list of available models with lora_model_id = "FFusion/400GB-LoraXL"
:
lora_filename =
- FFai.0001.4Guofeng4xl_V1125d.lora_Dim64.safetensors
- FFai.0002.4Guofeng4xl_V1125d.lora_Dim8.safetensors
- FFai.0003.4Guofeng4xl_V1125d.loraa.safetensors
- FFai.0004.Ambiencesdxl_A1.lora.safetensors
- FFai.0005.Ambiencesdxl_A1.lora_8.safetensors
- FFai.0006.Angrasdxl10_V22.lora.safetensors
- FFai.0007.Animaginexl_V10.lora.safetensors
- FFai.0008.Animeartdiffusionxl_Alpha3.lora.safetensors
- FFai.0009.Astreapixiexlanime_V16.lora.safetensors
- FFai.0010.Bluepencilxl_V010.lora.safetensors
- FFai.0011.Bluepencilxl_V021.lora.safetensors
- FFai.0012.Breakdomainxl_V03d.lora.safetensors
- FFai.0013.Canvasxl_Bfloat16v002.lora.safetensors
- FFai.0014.Cherrypickerxl_V20.lora.safetensors
- FFai.0015.Copaxtimelessxlsdxl1_V44.lora.safetensors
- FFai.0016.Counterfeitxl-Ffusionai-Alpha-Vae.lora.safetensors
- FFai.0017.Counterfeitxl_V10.lora.safetensors
- FFai.0018.Crystalclearxl_Ccxl.lora.safetensors
- FFai.0019.Deepbluexl_V006.lora.safetensors
- FFai.0020.Dream-Ffusion-Shaper.lora.safetensors
- FFai.0021.Dreamshaperxl10_Alpha2xl10.lora.safetensors
- FFai.0022.Duchaitenaiartsdxl_V10.lora.safetensors
- FFai.0023.Dynavisionxlallinonestylized_Beta0371bakedvae.lora.safetensors
- FFai.0024.Dynavisionxlallinonestylized_Beta0411bakedvae.lora.safetensors
- FFai.0025.Fantasticcharacters_V55.lora.safetensors
- FFai.0026.Fenrisxl_V55.lora.safetensors
- FFai.0027.Fudukimix_V10.lora.safetensors
- FFai.0028.Infinianimexl_V16.lora.safetensors
- FFai.0029.Juggernautxl_Version1.lora_1.safetensors
- FFai.0030.Lahmysterioussdxl_V330.lora.safetensors
- FFai.0031.Mbbxlultimate_V10rc.lora.safetensors
- FFai.0032.Miamodelsfwnsfwsdxl_V30.lora.safetensors
- FFai.0033.Morphxl_V10.lora.safetensors
- FFai.0034.Nightvisionxlphotorealisticportrait_Beta0681bakedvae.lora_1.safetensors
- FFai.0035.Osorubeshialphaxl_Z.lora.safetensors
- FFai.0036.Physiogenxl_V04.lora.safetensors
- FFai.0037.Protovisionxlhighfidelity3d_Beta0520bakedvae.lora.safetensors
- FFai.0038.Realitycheckxl_Alpha11.lora.safetensors
- FFai.0039.Realmixxl_V10.lora.safetensors
- FFai.0040.Reproductionsdxl_V31.lora.safetensors
- FFai.0041.Rundiffusionxl_Beta.lora.safetensors
- FFai.0042.Samaritan3dcartoon_V40sdxl.lora.safetensors
- FFai.0043.Sdvn6realxl_Detailface.lora.safetensors
- FFai.0044.Sdvn7realartxl_Beta2.lora.safetensors
- FFai.0045.Sdxl10arienmixxlasian_V10.lora.safetensors
- FFai.0046.Sdxlbasensfwfaces_Sdxlnsfwfaces03.lora.safetensors
- FFai.0047.Sdxlfaetastic_V10.lora.safetensors
- FFai.0048.Sdxlfixedvaefp16remove_Basefxiedvaev2fp16.lora.safetensors
- FFai.0049.Sdxlnijiv4_Sdxlnijiv4.lora.safetensors
- FFai.0050.Sdxlronghua_V11.lora.safetensors
- FFai.0051.Sdxlunstablediffusers_V5unchainedslayer.lora.safetensors
- FFai.0052.Sdxlyamersanimeultra_Yamersanimev2.lora.safetensors
- FFai.0053.Shikianimexl_V10.lora.safetensors
- FFai.0054.Spectrumblendx_V10.lora.safetensors
- FFai.0055.Stablediffusionxl_V30.lora.safetensors
- FFai.0056.Talmendoxlsdxl_V11beta.lora.safetensors
- FFai.0057.Wizard_V10.lora.safetensors
- FFai.0058.Wyvernmix15xl_Xlv11.lora.safetensors
- FFai.0059.Xl13asmodeussfwnsfw_V17bakedvae.lora.safetensors
- FFai.0060.Xl3experimentalsd10xl_V10.lora.safetensors
- FFai.0061.Xl6hephaistossd10xlsfw_V21bakedvaefp16fix.lora.safetensors
- FFai.0062.Xlperfectdesign_V2ultimateartwork.lora.safetensors
- FFai.0063.Xlyamersrealistic_V3.lora.safetensors
- FFai.0064.Xxmix9realisticsdxl_Testv20.lora.safetensors
- FFai.0065.Zavychromaxl_B2.lora.safetensors
π Acknowledgements & Citations
A huge shoutout to the community for their continued support and feedback. Together, we are pushing the boundaries of what's possible with machine learning!
We would also like to acknowledge and give credit to the following projects and authors:
- ComfyUI: We've used and modified portions of ComfyUI for our work.
- kohya-ss/sd-scripts and bmaltais: Our work also incorporates modifications from kohya-ss/sd-scripts.
- lora-inspector: We've benefited from the lora-inspector project.
- KohakuBlueleaf: Special mention to KohakuBlueleaf for their invaluable contributions.
HowMuch ???
Have you ever asked yourself, "How much space have I wasted on *.ckpt
and *.safetensors
checkpoints?" π€
Say hello to HowMuch: Checking checkpoint wasted space since... well, now!
π Enjoy this somewhat unnecessary, yet "fun-for-the-whole-family" DiskSpaceAnalyzer tool. π
Overview
HowMuch
is a Python tool designed to scan your drives (or a specified directory) and report on the total space used by files with specific extensions, mainly .ckpt
and .safetensors
.
It outputs:
- The total storage capacity of each scanned drive or directory.
- The space occupied by
.ckpt
and.safetensors
files. - The free space available.
- A neat bar chart visualizing the above data.
Installation
From PyPI
You can easily install HowMuch
via pip:
pip install howmuch
From Source
Clone the repository:
git clone https://github.com/1e-2/HowMuch.git
Navigate to the cloned directory and install:
cd HowMuch pip install .
Usage
Run the tool without any arguments to scan all drives:
howmuch
Or, specify a particular directory or drive to scan:
howmuch --scan C:
π Contact Information
The FFusion.ai project is proudly maintained by Source Code Bulgaria Ltd & Black Swan Technologies.
π§ Reach us at di@ffusion.ai for any inquiries or support.
π Find us on:
- π GitHub
- π Hugging Face
- π‘ Civitai
π Security powered by Comodo.BG & Preasidium.CX π Marketing by ΠΡΠ³ΡΠ».com π© π Sofia Istanbul London
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!
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