Remove Inference Engine Remove Large Language Models Remove LLM
article thumbnail

The Best Inference APIs for Open LLMs to Enhance Your AI App

Unite.AI

Imagine this: you have built an AI app with an incredible idea, but it struggles to deliver because running large language models (LLMs) feels like trying to host a concert with a cassette player. This is where inference APIs for open LLMs come in. The potential is there, but the performance?

LLM 278
article thumbnail

Design Patterns in Python for AI and LLM Engineers: A Practical Guide

Unite.AI

For AI and large language model (LLM) engineers , design patterns help build robust, scalable, and maintainable systems that handle complex workflows efficiently. This article dives into design patterns in Python, focusing on their relevance in AI and LLM -based systems. model hyperparameters).

Python 147
professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Layer-of-Thoughts Prompting (LoT): A Unique Approach that Uses Large Language Model (LLM) based Retrieval with Constraint Hierarchies

Marktechpost

Utilizing Large Language Models (LLMs) through different prompting strategies has become popular in recent years. Differentiating prompts in multi-turn interactions, which involve several exchanges between the user and model, is a crucial problem that remains mostly unresolved.

article thumbnail

PowerInfer: Fast Large Language Model Serving with a Consumer-grade GPU

Unite.AI

Due to their exceptional content creation capabilities, Generative Large Language Models are now at the forefront of the AI revolution, with ongoing efforts to enhance their generative abilities. However, despite rapid advancements, these models require substantial computational power and resources. Let's begin.

article thumbnail

Meet PowerInfer: A Fast Large Language Model (LLM) on a Single Consumer-Grade GPU that Speeds up Machine Learning Model Inference By 11 Times

Marktechpost

Generative Large Language Models (LLMs) are well known for their remarkable performance in a variety of tasks, including complex Natural Language Processing (NLP), creative writing, question answering, and code generation. times faster than the current llama.cpp system while retaining model fidelity.

article thumbnail

SPARE: Training-Free Representation Engineering for Managing Knowledge Conflicts in Large Language Models

Marktechpost

Large Language Models (LLMs) have demonstrated impressive capabilities in handling knowledge-intensive tasks through their parametric knowledge stored within model parameters. Representation engineering emerged as a higher-level framework for understanding LLM behavior at scale. Check out the Paper.

article thumbnail

WorFBench: A Benchmark for Evaluating Complex Workflow Generation in Large Language Model Agents

Marktechpost

Large Language Models (LLMs) have shown remarkable potential in solving complex real-world problems, from function calls to embodied planning and code generation. Researchers from Zhejiang University and Alibaba Group have proposed WORFBENCH, a benchmark for evaluating workflow generation capabilities in LLM agents.