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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. Upon evaluation, PowerInfer has also shown that it has the capability to run up to 11.69

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Google AI Research Introduces Process Advantage Verifiers: A Novel Machine Learning Approach to Improving LLM Reasoning Capabilities

Marktechpost

Large language models (LLMs) have become crucial in natural language processing, particularly for solving complex reasoning tasks. However, while LLMs can process and generate responses based on vast amounts of data, improving their reasoning capabilities is an ongoing challenge. Check out the Paper.

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SeedLM: A Post-Training Compression Method that Uses Pseudo-Random Generators to Efficiently Encode and Compress LLM Weights

Marktechpost

The ever-increasing size of Large Language Models (LLMs) presents a significant challenge for practical deployment. Despite their transformative impact on natural language processing, these models are often hindered by high memory transfer requirements, which pose a bottleneck during autoregressive generation.

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

Unite.AI

In this article, we will discuss PowerInfer, a high-speed LLM inference engine designed for standard computers powered by a single consumer-grade GPU. The PowerInfer framework seeks to utilize the high locality inherent in LLM inference, characterized by a power-law distribution in neuron activations.

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Deploying AI at Scale: How NVIDIA NIM and LangChain are Revolutionizing AI Integration and Performance

Unite.AI

NVIDIA Inference Microservices (NIM) and LangChain are two cutting-edge technologies that meet these needs, offering a comprehensive solution for deploying AI in real-world environments. Understanding NVIDIA NIM NVIDIA NIM, or NVIDIA Inference Microservices, is simplifying the process of deploying AI models.

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Self-Data Distilled Fine-Tuning: A Solution for Pruning and Supervised Fine-tuning Challenges in LLMs

Marktechpost

Large language models (LLMs) like GPT-4, Gemini, and Llama 3 have revolutionized natural language processing through extensive pre-training and supervised fine-tuning (SFT). However, these models come with high computational costs for training and inference. Check out the Paper.

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Baichuan-Omni: An Open-Source 7B Multimodal Large Language Model for Image, Video, Audio, and Text Processing

Marktechpost

LLMs such as LLaMA, MAP-Neo, Baichuan, Qwen, and Mixtral are trained on large amounts of text data, exhibiting strong capacities in natural language processing and task resolution through text generation capacity. It also provides multilingual support for languages such as English and Chinese.