Remove 2024 Remove Inference Engine Remove Large Language Models
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Katanemo Open Sources Arch-Function: A Set of Large Language Models (LLMs) Promising Ultra-Fast Speeds at Function-Calling Tasks for Agentic Workflows

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One of the biggest hurdles organizations face is implementing Large Language Models (LLMs) to handle intricate workflows effectively. Issues of speed, flexibility, and scalability often hinder the automation of complex workflows requiring coordination across multiple systems. If you like our work, you will love our newsletter.

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SimLayerKV: An Efficient Solution to KV Cache Challenges in Large Language Models

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Recent advancements in large language models (LLMs) have significantly enhanced their ability to handle long contexts, making them highly effective in various tasks, from answering questions to complex reasoning. If you like our work, you will love our newsletter. Don’t Forget to join our 50k+ ML SubReddit.

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Salesforce AI Introduces ReGenesis: A Novel AI Approach to Improving Large Language Model Reasoning Capabilities

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Large language models (LLMs) have revolutionized how machines process and generate human language, but their ability to reason effectively across diverse tasks remains a significant challenge. If you like our work, you will love our newsletter. Don’t Forget to join our 50k+ ML SubReddit.

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aiXcoder-7B: A Lightweight and Efficient Large Language Model Offering High Accuracy in Code Completion Across Multiple Languages and Benchmarks

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Large language models (LLMs) have revolutionized various domains, including code completion, where artificial intelligence predicts and suggests code based on a developer’s previous inputs. Despite the promise of LLMs, many models struggle with balancing speed and accuracy. Don’t Forget to join our 50k+ ML SubReddit.

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

Marktechpost

Recent advancements in Large Language Models (LLMs) have reshaped the Artificial intelligence (AI)landscape, paving the way for the creation of Multimodal Large Language Models (MLLMs). If you like our work, you will love our newsletter. Don’t Forget to join our 50k+ ML SubReddit.

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Harnessing Introspection in AI: How Large Language Models Are Learning to Understand and Predict Their Behavior for Greater Accuracy

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Large Language models (LLMs) have long been trained to process vast amounts of data to generate responses that align with patterns seen during training. If you like our work, you will love our newsletter. Don’t Forget to join our 50k+ ML SubReddit.

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This AI Paper from Meta AI Highlights the Risks of Using Synthetic Data to Train Large Language Models

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Upcoming Live Webinar- Oct 29, 2024] The Best Platform for Serving Fine-Tuned Models: Predibase Inference Engine (Promoted) The post This AI Paper from Meta AI Highlights the Risks of Using Synthetic Data to Train Large Language Models appeared first on MarkTechPost.