Back

Fine-Tuning: The Secret Sauce of AI Magic! Ever wonder how AI gets so smart? It’s all about fine-tuning! Imagine a pre-trained model as a genius with general knowledge. 🧠✨ Fine-tuning takes that genius and hones its skills for a specific task, li

Hiring AI/ML Engineer 🚀 Join us to shape the future of AI. Work hands-on with LLMs, transformers, and cutting-edge architectures. Drive breakthroughs in model training, fine-tuning, and deployment that directly influence product and research outcom

X updates its developer agreement to ban third parties from using the X API or X Content for training or fine-tuning foundation or frontier AI models.

"A Survey on Post-Training of Large Language Models" This paper systematically categorizes post-training into five major paradigms: 1. Fine-Tuning 2. Alignment 3. Reasoning Enhancement 4. Efficiency Optimization 5. Integration & Adaptation 1️⃣ Fin

Testing our Voice Clone Model in Friday — built just last night! Fingers crossed it performs well at the bench targets today. Let’s make this moment count.❤

"Just fine-tuned LLaMA 3.2 using Apple's MLX framework and it was a breeze! The speed and simplicity were unmatched. Here's the LoRA command I used to kick off training: ``` python lora.py \ --train \ --model 'mistralai/Mistral-7B-Instruct-v0.2' \ -

I fine-tuned 3 models this week to understand why people fail. Used LLaMA-2-7B, Mistral-7B, and Phi-2. Different datasets. Different methods (full tuning vs LoRA vs QLoRA). Here's what I learned that nobody talks about: 1. Data quality > Data quan

Overfitting, underfitting, and fitting — these aren't just technical terms, but critical checkpoints in every machine learning workflow. Understanding these concepts is key to evaluating model behavior, improving generalization, and building solutio

Another open-source model has arrived, and it’s even better than DeepSeek-V3. The Allen Institute for AI just introduced Tülu 3 (405B) 🐫, a post-training model that is a fine-tune of Llama 3.1 405B, which outperforms DeepSeek V3.