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alvdansen
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flux-koda
#StableDiffusion #Flux #AI #ComfyUI
Model description
Koda captures the nostalgic essence of early 1990s photography, evoking memories of disposable cameras and carefree travels. It specializes in creating images with a distinct vintage quality, characterized by slightly washed-out colors, soft focus, and the occasional light leak or film grain. The model excels at producing slice-of-life scenes that feel spontaneous and candid, as if plucked from a family photo album or a backpacker's travel diary.
Words that can highlight interesting nuances within the model:
kodachrome, blurry, realistic, still life, depth of field, scenery, no humans, monochrome, greyscale, traditional media, horizon, looking at viewer, light particles, shadow
https://cdn-uploads.huggingface.co/production/uploads/635dd6cd4fabde0df74aeae6/7CqMzFOlH6yoM-NpQdYDs.png
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flux-koda
#StableDiffusion #Flux #AI #ComfyUI
Model description
Koda captures the nostalgic essence of early 1990s photography, evoking memories of disposable cameras and carefree travels. It specializes in creating images with a distinct vintage quality, characterized by slightly washed-out colors, soft focus, and the occasional light leak or film grain. The model excels at producing slice-of-life scenes that feel spontaneous and candid, as if plucked from a family photo album or a backpacker's travel diary.
Words that can highlight interesting nuances within the model:
kodachrome, blurry, realistic, still life, depth of field, scenery, no humans, monochrome, greyscale, traditional media, horizon, looking at viewer, light particles, shadow
https://cdn-uploads.huggingface.co/production/uploads/635dd6cd4fabde0df74aeae6/7CqMzFOlH6yoM-NpQdYDs.png
Welcome to our interactive tutorial on Flux DreamBooth LoRA!
We will be exploring the concept of LoRA (Low-Rank Adaptation) in the context of DreamBooth, a text-to-image synthesis model. Specifically, we will be working with the linoyts/3d_icon_flux_1500 DreamBooth LoRA weights for the black-forest-labs/FLUX.1-dev model.
What would you like to learn about?
Model Description: Understand the context and training process of the Flux DreamBooth LoRA model.
LoRA and its Applications: Learn about the concept of LoRA and its use cases in text-to-image synthesis.
Trigger Words and Image Generation: Discover how to use trigger words to generate images with the Flux DreamBooth LoRA model.
Loading and Using the Model: Understand how to load and use the linoyts/3d_icon_flux_1500 DreamBooth LoRA weights with the diffusers library.
Limitations and Bias: Explore the potential limitations and biases of the model, as well as strategies for addressing them.
Training Details: Learn about the data used to train the model and its implications for the generated images.
Please select one of the above options by typing the corresponding number.
https://huggingface.co/linoyts/3d_icon_flux_1500#flux-dreambooth-lora---linoyts3d_icon_flux_1500
We will be exploring the concept of LoRA (Low-Rank Adaptation) in the context of DreamBooth, a text-to-image synthesis model. Specifically, we will be working with the linoyts/3d_icon_flux_1500 DreamBooth LoRA weights for the black-forest-labs/FLUX.1-dev model.
What would you like to learn about?
Model Description: Understand the context and training process of the Flux DreamBooth LoRA model.
LoRA and its Applications: Learn about the concept of LoRA and its use cases in text-to-image synthesis.
Trigger Words and Image Generation: Discover how to use trigger words to generate images with the Flux DreamBooth LoRA model.
Loading and Using the Model: Understand how to load and use the linoyts/3d_icon_flux_1500 DreamBooth LoRA weights with the diffusers library.
Limitations and Bias: Explore the potential limitations and biases of the model, as well as strategies for addressing them.
Training Details: Learn about the data used to train the model and its implications for the generated images.
Please select one of the above options by typing the corresponding number.
https://huggingface.co/linoyts/3d_icon_flux_1500#flux-dreambooth-lora---linoyts3d_icon_flux_1500
huggingface.co
linoyts/3d_icon_flux_1500 · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
2024.8.8FLUX.1-DEV Canny - a Hugging Face Space by DamarJati
metadata
title: FLUX.1-DEV Canny
emoji: 🧋
colorFrom: pink
colorTo: purple
sdk: gradio
sdk_version: 4.40.0
app_file: app.py
pinned: true
short_description: FLUX Dev - Controlnet Canny
https://github.com/XLabs-AI/x-flux.git
https://huggingface.co/spaces/DamarJati/FLUX.1-DEV-Canny
#Flux #Controlnet
metadata
title: FLUX.1-DEV Canny
emoji: 🧋
colorFrom: pink
colorTo: purple
sdk: gradio
sdk_version: 4.40.0
app_file: app.py
pinned: true
short_description: FLUX Dev - Controlnet Canny
https://github.com/XLabs-AI/x-flux.git
https://huggingface.co/spaces/DamarJati/FLUX.1-DEV-Canny
#Flux #Controlnet
GitHub
GitHub - XLabs-AI/x-flux
Contribute to XLabs-AI/x-flux development by creating an account on GitHub.
Flux Examples | ComfyUI_examples workflows
Regular Full Version
Files to download for the regular version
If you don’t have t5xxl_fp16.safetensors or clip_l.safetensors already in your ComfyUI/models/clip/ directory you can find them on: this link. You can use t5xxl_fp8_e4m3fn.safetensors instead for lower memory usage but the fp16 one is recommended if you have more than 32GB ram.
The VAE can be found here and should go in your ComfyUI/models/vae/ folder.
Tips if you are running out of memory:
Use the single file fp8 version that you can find by looking Below
You can set the weight_dtype in the “Load Diffusion Model” node to fp8 which will lower the memory usage by half but might reduce quality a tiny bit. You can also download the example.
Flux Dev
You can find the Flux Dev diffusion model weights here. Put the flux1-dev.safetensors file in your: ComfyUI/models/unet/ folder.
You can then load or drag the following image in ComfyUI to get the workflow:
Flux Schnell
Flux Schnell is a distilled 4 step model.
You can find the Flux Schnell diffusion model weights here this file should go in your: ComfyUI/models/unet/ folder.
You can then load or drag the following image in ComfyUI to get the workflow:
Simple to use FP8 Checkpoint version
Flux Dev
You can find an easy to use checkpoint for the Flux dev here that you can put in your: ComfyUI/models/checkpoints/ directory.
This file can be loaded with the regular “Load Checkpoint” node. Make sure you set CFG to 1.0 when using it.
Note that fp8 degrades the quality a bit so if you have the resources the official full 16 bit version is recommended.
You can then load or drag the following image in ComfyUI to get the workflow:
Flux Schnell
For Flux schnell you can get the checkpoint here that you can put in your: ComfyUI/models/checkpoints/ directory.
You can then load or drag the following image in ComfyUI to get the workflow: https://comfyanonymous.github.io/ComfyUI_examples/flux/ #Flux
Regular Full Version
Files to download for the regular version
If you don’t have t5xxl_fp16.safetensors or clip_l.safetensors already in your ComfyUI/models/clip/ directory you can find them on: this link. You can use t5xxl_fp8_e4m3fn.safetensors instead for lower memory usage but the fp16 one is recommended if you have more than 32GB ram.
The VAE can be found here and should go in your ComfyUI/models/vae/ folder.
Tips if you are running out of memory:
Use the single file fp8 version that you can find by looking Below
You can set the weight_dtype in the “Load Diffusion Model” node to fp8 which will lower the memory usage by half but might reduce quality a tiny bit. You can also download the example.
Flux Dev
You can find the Flux Dev diffusion model weights here. Put the flux1-dev.safetensors file in your: ComfyUI/models/unet/ folder.
You can then load or drag the following image in ComfyUI to get the workflow:
Flux Schnell
Flux Schnell is a distilled 4 step model.
You can find the Flux Schnell diffusion model weights here this file should go in your: ComfyUI/models/unet/ folder.
You can then load or drag the following image in ComfyUI to get the workflow:
Simple to use FP8 Checkpoint version
Flux Dev
You can find an easy to use checkpoint for the Flux dev here that you can put in your: ComfyUI/models/checkpoints/ directory.
This file can be loaded with the regular “Load Checkpoint” node. Make sure you set CFG to 1.0 when using it.
Note that fp8 degrades the quality a bit so if you have the resources the official full 16 bit version is recommended.
You can then load or drag the following image in ComfyUI to get the workflow:
Flux Schnell
For Flux schnell you can get the checkpoint here that you can put in your: ComfyUI/models/checkpoints/ directory.
You can then load or drag the following image in ComfyUI to get the workflow: https://comfyanonymous.github.io/ComfyUI_examples/flux/ #Flux
🔗 Comprehensive Tutorial Video Link ▶️ https://youtu.be/bupRePUOA18
FLUX represents a milestone in open source txt2img technology, delivering superior quality and more accurate prompt adherence than #Midjourney, Adobe Firefly, Leonardo Ai, Playground Ai, Stable Diffusion, SDXL, SD3, and Dall E3. #FLUX, a creation of Black Forest Labs, boasts a team largely comprised of #StableDiffusion's original developers, and its output quality is truly remarkable. This statement is not hyperbole; you'll witness its capabilities in the tutorial. This guide will demonstrate how to effortlessly install and utilize FLUX models on your personal computer and cloud platforms like Massed Compute, RunPod, and a complimentary Kaggle account.
🔗 FLUX Setup Guide (publicly accessible) ⤵️
▶️ https://www.patreon.com/posts/106135985
🔗 FLUX Models One-Click Robust Automatic Downloader Scripts ⤵️
▶️ https://www.patreon.com/posts/109289967
🔗 Primary Windows SwarmUI Tutorial (Essential for Usage Instructions) ⤵️
▶️ https://youtu.be/HKX8_F1Er_w
🔗 Cloud-based SwarmUI Tutorial (Massed Compute - RunPod - Kaggle) ⤵️
▶️ https://youtu.be/XFUZof6Skkw
🔗 SECourses Discord Server for Comprehensive Support ⤵️
▶️ https://discord.com/servers/software-engineering-courses-secourses-772774097734074388
🔗 SECourses Reddit Community ⤵️
▶️ https://www.reddit.com/r/SECourses/
🔗 SECourses GitHub Repository ⤵️
▶️ https://github.com/FurkanGozukara/Stable-Diffusion
🔗 Official FLUX 1 Launch Announcement Blog Post ⤵️
▶️ https://blackforestlabs.ai/announcing-black-forest-labs/
Video Segments
0:00 Introduction to the state-of-the-art open source txt2img model FLUX
5:01 Process for integrating FLUX model into SwarmUI
FLUX represents a milestone in open source txt2img technology, delivering superior quality and more accurate prompt adherence than #Midjourney, Adobe Firefly, Leonardo Ai, Playground Ai, Stable Diffusion, SDXL, SD3, and Dall E3. #FLUX, a creation of Black Forest Labs, boasts a team largely comprised of #StableDiffusion's original developers, and its output quality is truly remarkable. This statement is not hyperbole; you'll witness its capabilities in the tutorial. This guide will demonstrate how to effortlessly install and utilize FLUX models on your personal computer and cloud platforms like Massed Compute, RunPod, and a complimentary Kaggle account.
🔗 FLUX Setup Guide (publicly accessible) ⤵️
▶️ https://www.patreon.com/posts/106135985
🔗 FLUX Models One-Click Robust Automatic Downloader Scripts ⤵️
▶️ https://www.patreon.com/posts/109289967
🔗 Primary Windows SwarmUI Tutorial (Essential for Usage Instructions) ⤵️
▶️ https://youtu.be/HKX8_F1Er_w
🔗 Cloud-based SwarmUI Tutorial (Massed Compute - RunPod - Kaggle) ⤵️
▶️ https://youtu.be/XFUZof6Skkw
🔗 SECourses Discord Server for Comprehensive Support ⤵️
▶️ https://discord.com/servers/software-engineering-courses-secourses-772774097734074388
🔗 SECourses Reddit Community ⤵️
▶️ https://www.reddit.com/r/SECourses/
🔗 SECourses GitHub Repository ⤵️
▶️ https://github.com/FurkanGozukara/Stable-Diffusion
🔗 Official FLUX 1 Launch Announcement Blog Post ⤵️
▶️ https://blackforestlabs.ai/announcing-black-forest-labs/
Video Segments
0:00 Introduction to the state-of-the-art open source txt2img model FLUX
5:01 Process for integrating FLUX model into SwarmUI