Why fine-tune LLMs? GPT-4o fine-tune for PERFECT FLUX Image Prompts

Fine-Tuning SOTA GPT-4o: You probably don't need it - BUT when you do, here's how to do it.

🔗 Reusable OpenAI Fine-Tune Codebase

🔗 Black Forest Labs

🧠 OpenAI GPT-4o Fine-Tune

🧠 Replicate Black Forest Labs Flux-Pro

🚀 Welcome back, engineers! In this video, we dive into the incredible world of fine-tuning with the newly released GPT-4o. Have you ever wondered why you should fine-tune a model and when it makes sense to do so? We’ve got you covered!

🔥 We’ll start with a discussion of the state-of-the-art fine-tuned GPT-4o model by Cosine Genie (ai software engineer) that’s setting new benchmarks on the software engineering verified benchmark. Discover how fine-tuning can bring game-changing performance gains and cost savings, potentially transforming your applications from good to exceptional.

🛠️ Here’s what you can expect:
- Legit Fine-Tuned Use Case: See a real-world application of a fine-tuned GPT-4o model.
- When and Why to Fine-Tune: Understand the key scenarios where fine-tuning can be beneficial.
- Fine-Tuned Code Base: Get hands-on with a code base designed for fine-tuning any OpenAI model, including the latest GPT-4o.

📸 We’ll showcase "Vision Grid", an unreleased tool that uses fine-tuned GPT-4o to create stunning image prompts. Watch as we generate INSANELY, STUPIDLY, high-quality images using Black Forest Labs' Flux 1 image generation models, demonstrating the power of fine-tuned models in action.

💡 We're talking prompt to prompt to images so whether you’re a prompt engineer, AI enthusiast, or software developer, this video is packed with insights on leveraging fine-tuning to enhance your GenAI projects. Learn how to reduce token usage, handle complex domain-specific tasks, and achieve consistently specific outputs.

👍 Hit the like button, subscribe, and join us on this journey as we push the boundaries of generative AI. Stay ahead of the curve with cutting-edge techniques and practical applications that make your work more impactful and efficient.

🛠️ Bonus: Get access to our reusable OpenAI fine-tuning codebase to jumpstart your own projects!

🍓🍓 Fusion Prompt Chain

🍓 Prompt Chaining

#promptengineering #midjourney #llm

[KyleFES]

Legend IndyDevDan, loving the uploads G 🧐

[stereotyp]

I just started training LoRAs for Flux. This is so much fun. You have to try this!

[Adrian_Galilea]

In order to validate how good the results are you should compare the image generations of your original prompt vs the expanded gpt4o fine-tuned prompt. Some image models are very good with anemic prompts so the only way to evaluate would be comparing both of them. (I have done this in the past)

Love your channel, share it constantly, keep it up <3

[techfixer]

DevDan...you've got a new subscriber with me! Great content, need to binge your vidz. Your unreleased tool "Vision Grid" rocks! Do you plan to make it available in th future? Also, I learned a great deal in your other vid on Cursor AI. Thnk you hermano! Props and high-five to you! 🖐️

[Nadia-AIInsiders]

Did you put your long instructions into a system prompt while fine-tuning? If yes, don’t you need to use the same system prompt when using the model, or does it work well without the system prompt after the tuning? I’ve experimented with fine-tuning 4o mini and 4o for content creation — it works much better than few-shot prompting, and the model captures the creator’s style really well, making fine-tuning an ideal choice for scaling content :)

[monkeyfish]

What hardware were you using to generate these sky diving pics? Was this in ‘realtime’? I am in for getting a new macbook at the end of this month and wonder what would work best.

[mrschmiklz]

This is flux fine tuned specific gpt4o? What docs for the fine tune, if you know... Every image gen model will have specific keywords and formatting, correct?

[TaskSwitcherify]

What is the max. resolution of images out of Flux? Also, won't your prompt-expanding feature convert people's unique and original prompts into the same "expanded" prompts for everyone? Thanks

[amit]

Hi, nice video. Will you be able to share the dataset you used for finetuning?

[newfrontiers]

But don't the fine tuned models cost like 5x more via the API?

[MacSn]

Couldn't you have got the same result using a prompt that takes your input and generate a detailed prompt for flux?

[mrschmiklz]

apologies. i am commenting as i am watching. so generic instructions and not img gen specific model instructions. would be interested in seeing model specific fine tuning as, to my knowledge, most models are trained differently with keywords and formatting of prompts can be different