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Customize GPT-4o mini for your application with fine-tuning. Available today to tier 4 and 5 users, we plan to gradually expand access to all tiers. First 2M training tokens a day are free, through Sept 23.

OpenAI Developers

375,675 subscribers

920,828 görüntüleme • 2 yıl önce •via X (Twitter)

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TestingCatalog News 🗞 profil fotoğrafı

TestingCatalog News 🗞2 yıl önce

For a second I was expecting Llama 3.1 405B integration announcement 😅

CHOI profil fotoğrafı

CHOI2 yıl önce

🤣🤣

Cloud Seeder profil fotoğrafı

Cloud Seeder2 yıl önce

dude i dont even know about these teirs.. im just an old beta user<3

albs — 3/staccs profil fotoğrafı

albs — 3/staccs2 yıl önce

ayo mah, not to brag, but i'm tier 5

Stephen profil fotoğrafı

Stephen2 yıl önce

mini finetuning is fast. 4o is better, but for cost and speed, it’s great. here’s an economist headline writer…

Pablo Huichalaf profil fotoğrafı

Pablo Huichalaf2 yıl önce

Great... When voice mode?

Diego | AI 🚀 - e/acc profil fotoğrafı

Diego | AI 🚀 - e/acc2 yıl önce

Not on Llama day boys

Gourav (building quickest AI extension) profil fotoğrafı

Gourav (building quickest AI extension)2 yıl önce

what are some use cases of fine tuning for B2C products?

vilsinho profil fotoğrafı

vilsinho2 yıl önce

Just use llama

Risphere profil fotoğrafı

Risphere2 yıl önce

Please make fine-tuning available for tier 1, 2 and 3!

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Remember reinforcement fine-tuning? We’ve been working away at it since last December, and it’s available today with OpenAI o4-mini! RFT uses chain-of-thought reasoning and task-specific grading to improve model performance—especially useful for complex domains. Take Accordance, which used RFT to fine-tune a model that’s SOTA for their tax and accounting purposes. And in supervised fine-tuning news: you can now fine-tune GPT-4.1 nano. Get even more from our fastest, cheapest model by training it specifically for your use-case.

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Openai giving $50,000 in FREE API credits and it's hidden in your account settings 😳 most people have no idea this exists what you get every single day: - 250K tokens/day for GPT-5.5 and GPT-5.2 (powerful models) - 2.5M tokens/day for GPT-5.1-Mini and GPT-5-Nano (lighter models) - up to 10M tokens/day if you're on tier 3-5 not a one time lump sum, it resets daily it's called the data sharing program and here's how it works: > go to > click data controls → sharing > opt in to both options > done, free daily tokens activate immediately important note: - your data gets used by openai for training and improvements - don't use it for client work or anything sensitive - need a positive account balance to activate perfect for: - learning and experimenting - side projects and personal builds - testing new models without paying you need a positive account balance to activate it but after that it's free every day save this and take free 50k credits before they close it

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An exciting new course: Fine-tuning and Reinforcement Learning for LLMs: Intro to Post-training, taught by Sharon Zhou, VP of AI at AMD. Available now at Post-training is the key technique used by frontier labs to turn a base LLM--a model trained on massive unlabeled text to predict the next word/token--into a helpful, reliable assistant that can follow instructions. I've also seen many applications where post-training is what turns a demo application that works only 80% of the time into a reliable system that consistently performs. This course will teach you the most important post-training techniques! In this 5 module course, Sharon walks you through the complete post-training pipeline: supervised fine-tuning, reward modeling, RLHF, and techniques like PPO and GRPO. You'll also learn to use LoRA for efficient training, and to design evals that catch problems before and after deployment. Skills you'll gain: - Apply supervised fine-tuning and reinforcement learning (RLHF, PPO, GRPO) to align models to desired behaviors - Use LoRA for efficient fine-tuning without retraining entire models - Prepare datasets and generate synthetic data for post-training - Understand how to operate LLM production pipelines, with go/no-go decision points and feedback loops These advanced methods aren’t limited to frontier AI labs anymore, and you can now use them in your own applications. Learn here:

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132,304 görüntüleme • 9 ay önce

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265,761 görüntüleme • 3 ay önce

OpenAI engineer explained every form of fine-tuning in 1 hour 46 minutes - better than $3000 fine-tuning bootcamps. pick your task -> try prompting first -> drop to SFT for style -> run DPO for preference -> run RFT for verifiable rewards -> ship a model 10x cheaper than GPT-5. That loop is why teams that fine-tune beat teams that only prompt on cost and speed. Prompting + SFT + DPO + RFT + OpenAI fine-tuning API - that's the stack. Watch and save it, then pick the right fine-tune for your task this week.

OpenAI engineer explained every form of fine-tuning in 1 hour 46 minutes - better than $3000 fine-tuning bootcamps. pick your task -> try prompting first -> drop to SFT for style -> run DPO for preference -> run RFT for verifiable rewards -> ship a model 10x cheaper than GPT-5. That loop is why teams that fine-tune beat teams that only prompt on cost and speed. Prompting + SFT + DPO + RFT + OpenAI fine-tuning API - that's the stack. Watch and save it, then pick the right fine-tune for your task this week.

h100envy

41,195 görüntüleme • 1 ay önce