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CMU Researchers Introduce ReLM: An AI System For Validating And Querying LLMs Using Standard Regular Expressions

Marktechpost

For the ever-growing challenge of LLM validation, ReLM provides a competitive and generalized starting point. ReLM is the first solution that allows practitioners to directly measure LLM behavior over collections too vast to enumerate by describing a query as the whole set of test patterns.

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Spark NLP 5.0: It’s All About That Search!

John Snow Labs

With this support, you can look forward to faster inference, automatic optimization, and quantization when exporting your LLM models. Additionally, we are also set to release an array of new LLM models fine-tuned specifically for chat and instruction, now that we have successfully integrated ONNX Runtime into Spark NLP.

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No More Paid Endpoints: How to Create Your Own Free Text Generation Endpoints with Ease

Mlearning.ai

One of the biggest challenges of using LLMs is the cost of accessing them. Many LLMs, such as OpenAI’s GPT-3, are only available through paid APIs. Learn how to deploy any open-source LLM as a free API endpoint using HuggingFace and Gradio. Many LLMs, such as OpenAI’s GPT-3, are only available through paid APIs.

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ODSC’s AI Weekly Recap: Week of March 8th

ODSC - Open Data Science

gemma.cpp is a lightweight, standalone C++ inference engine for the Gemma foundation models from Google. They are text-to-text, decoder-only large language models, available in English, with open weights, pre-trained variants, and instruction-tuned variants.

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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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Start Up Your Engines: NVIDIA and Google Cloud Collaborate to Accelerate AI Development

NVIDIA

Teams from the companies worked closely together to accelerate the performance of Gemma — built from the same research and technology used to create Google DeepMind’s most capable model yet, Gemini — with NVIDIA TensorRT-LLM , an open-source library for optimizing large language model inference, when running on NVIDIA GPUs.

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Implementing Small Language Models (SLMs) with RAG on Embedded Devices Leading to Cost Reduction, Data Privacy, and Offline Use

deepsense.ai

Benefits of SLMs on Edge Devices In this section, we present three compelling reasons why companies may find Small Language Model (SLM) applications preferable to their cloud-heavy Large Language Model (LLM) counterparts: Cost Reduction The expense of cloud inference for Large Language Models can be prohibitive.