AI content generation is about feeding your AI models with semantic and contextual information. The result is a platform that can ‘understand’ what an item is, and how it should be used. AI creates content using semantic knowledge in any form of content including video, 3d, VR and more.
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Latest Artificial Intelligence Content News
3 Smart Ways to Encode Categorical Features for Machine Learning
If you spend any time working with real-world data, you quickly realize that not everything comes in neat, clean numbers.
Pretraining a Llama Model on Your Local GPU
This article is divided into three parts; they are: • Training a Tokenizer with Special Tokens • Preparing the Training Data • Running the Pretraining The model architecture you will use is the same as the one created in the
Rotary Position Embeddings for Long Context Length
This article is divided into two parts; they are: • Simple RoPE • RoPE for Long Context Length Compared to the sinusoidal position embeddings in the original Transformer paper, RoPE mutates the input tensor using a rotation matrix: $$ begin{aligned} X_{n,i} &= X_{n,i} cos(ntheta_i) – X_{n,frac{d}{2}+i} sin(ntheta_i) \ X_{n,frac{d}{2}+i} &=…
How to Fine-Tune a Local Mistral or Llama 3 Model on Your Own Dataset
Large language models (LLMs) like Mistral 7B and Llama 3 8B have shaken the AI field, but their broad nature limits their application to specialized areas.