Flux 1.1 Pro & Ultra Fine-Tuning API is HERE! + Custom Gradio UI Walkthrough
HTML-код
- Опубликовано: 24 янв 2025
- 🔗 Collaborate with me to unlock the potential of AI fine-tuning:
Book a free consultation 👉 calendly.com/a...
🌐 Visit my website:
autolynxai.com/
Exploring Flux Pro & Pro Ultra: Fine-Tuning AI Made Simple
In this video, we dive into the latest advancements in AI fine-tuning with Flux Pro and Pro Ultra, the flagship models released by Black Forest Labs. 🚀
I’ll walk you through the custom UI I built to make fine-tuning these powerful models more accessible than ever. Designed using Gradio and seamlessly integrated with Flux's API, this user-friendly interface enables you to:
✅ Select models for fine-tuning
✅ Configure training parameters for LoRA or full-model fine-tuning
✅ Upload datasets and monitor training progress in real-time
✅ Generate fine-tuned LoRA or fully trained models effortlessly
✅ Deploy and inference your customized models
Key Highlights of This Video:
🔍 In-Depth Look at Flux Pro & Pro Ultra
Explore the technical advancements of these cutting-edge models and their potential to revolutionize AI fine-tuning.
🛠️ Custom User Interface Built for Developers & Creators
A showcase of the Gradio-based UI designed to simplify access to the Flux Fine-Tuning API. No more command-line complexities - fine-tune models with ease!
📊 Real-World Applications of Fine-Tuned Models
Learn how LoRA adaptations and full fine-tuning can be applied across industries like automation, content creation, and research.
⚙️ Technologies Used:
Python backend for API integration
Gradio (v3.50.2) for an interactive UI
Flux Fine-Tuning API for LoRA and full-model customization
Resources & Links:
📘 Flux Fine-Tuning API Documentation:
blackforestlab...
📁 GitHub Repository for My Custom Flux UI Project:
github.com/You...
💡 Learn More About Black Forest Labs:
blackforestlab...
About Me:
At AutoLynx AI, we build intuitive AI tools that bridge the gap between technical complexity and real-world usability. Whether you're a developer, researcher, or content creator, we’re here to empower your AI journey.
Ready to transform your AI workflows? Book a free consultation today!
💡 calendly.com/a...
#AIFineTuning #FluxPro #aiinnovation #aiagents #generativeai #aiimages
#aiimagegenerator #aiimagegeneration #AIAutomation #OpenAI #n8n #Automation #BusinessAutomation #DocumentProcessing #WorkflowAutomation #AI #AIAgent #AutomatedBusiness #AITools #ai #aiforbusiness #aiagents #aiimage #finetune
![Blox Fruits Dragon Rework Update [Full Stream]](http://i.ytimg.com/vi/EqDAp8udhm0/mqdefault.jpg)
Thanks so much for this video! I've been experimenting with various parameters for training LoRAs and trying full fine-tuning as well. Interestingly, I found that full fine-tuning didn’t give me the results I was expecting. Even with LoRAs, increasing the training steps didn’t always improve the outputs. In fact, some of my best results came from models trained on fewer steps.
There's definitely a lot to figure out when it comes to optimizing parameters and finding what works best with this model. Your insights here have been really helpful!
Hi Paresh, thank you, amazing job, can you fix the link of your repo on git, its getting 404
Thank you for pointing that out! I’ve made some updates and tested the new system-it’s now working correctly. Please follow the ReadME.md steps to set it up, especially these steps:
-Rename config.example.json to config.json
-Add your Flux Pro API key to the config.json file.
-Ensure you’ve added credits to your Black Forest Labs account.
I also encountered a problem that makes the same sid although it is set to 0
Yeah, for random seed generation, You should leave the seed box empty.
Great video, I'm running into issues though with finetuning, I upload the zip, set the parameters and start fine tuning. It will generate a fine tune ID but then nothing happens, I've done multiple runs and my BFL balance just stays the same as well.
Hi, thank you for sharing your concern! I ran the training on another system, and it worked perfectly. However, here are a few things you might want to check to ensure everything runs smoothly:
Image Format:
The uploaded file should be a Base64-encoded .zip.
Inside the .zip, images must be in .PNG or .JPEG format. Ensure no other formats are included.
Checking the Status:
If you see an error like "Model not found" or "Invalid fine-tune ID", don’t worry! This is a minor bug and doesn’t affect the process.
If credits have been deducted from your account, it means the training has started and is running in the background.
Training Time:
The training process may take anywhere between 5 to 10 minutes (or sometimes a little longer), depending on the parameters used.
Once the training is complete, the status button will update to "Ready".
Troubleshooting Steps:
After starting the training, wait for 10 minutes, then check the status. If it’s still not ready, wait another 10 minutes and check again.
Make sure to use the correct file formats as mentioned above, and keep an eye on your credits.
I’m actively working on fixing the bug to ensure the status updates in real-time as the training progresses. In the meantime, please follow these steps, and everything should work as expected.
Please check the Terminal in your IDE as well, that might help you figure out the issue.
Let me know if you have any other questions or run into further issue.
why is there no raw in FLUX Pro 1.1 Ultra?
If I have a dataset with poor quality images but where the product is clearly visible, I get poor quality images on the output, but the old way of training lora did not distort the image quality even if the dataset in poor quality
I found that as well with these models, they really a on the provided dataset quality but also recreate the Fine-tuned object to have much more closer resemblance to the trained images compared to the dev model.
I guess it goes both ways, could work great for you if you have high quality data ,not so much if you don't.
@ Can you please tell me in which resolutions to save photos, because I recently did a large 4k and I got a very bad training and can you tell me if I can use a product png file without background for training? I didn't find it in the documentation.
@@deonix95 I’ve also struggled to find clear guidelines on the optimal resolution and formats for training. I’ve already sent a request to Black Forest Labs asking for more clarity on this, and I’ll definitely keep you updated if I hear back.
In the meantime, I’ve had decent results using 1024x1024 resolution images in PNG or JPEG format, similar to what I used with the Flux Dev model before. Hopefully, this helps you while we wait for further updates. I’ll also share any tweaks or updates on the UI to ensure it works seamlessly with this setup.
hi, can you add flux fill pro with lora also ?
Sure, Will be working on those soon!