Overview

  • Solar Pro Preview: The most intelligent LLM on a single GPU

  • Upstage Document Parse: Let LLMs read your documents with speed and accuracy

Introducing Solar Mini Chat ja: Expanding Language Support to Japanese
Tech (전영훈) YoungHoon Tech (전영훈) YoungHoon

Introducing Solar Mini Chat ja: Expanding Language Support to Japanese

We are thrilled to announce that Solar mini chat now includes Japanese, alongside English and Korean. Specially fine-tuned for multi-turn chat, Solar mini chat ja excels in Japanese language interactions, offering high performance and an enhanced user experience. Ideal for applications demanding nuanced and context-aware communication, it surpasses many open-source models in key NLP tasks. Seamlessly integrate it with your existing API keys and elevate your Japanese chat applications!

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Breaking Barriers: Revolutionize Your Work with Our Next-Level Embedding Model
Tech (전영훈) YoungHoon Tech (전영훈) YoungHoon

Breaking Barriers: Revolutionize Your Work with Our Next-Level Embedding Model

Experience the Next Leap in Embedding Technology with Solar Embedding-1-Large: Our groundbreaking Solar Embedding-1-Large model is set to transform your work processes. With superior performance compared to OpenAI's models and a commitment to tackling even the toughest tasks, it's time to elevate your search systems and beyond.

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Deploying Solar with BentoML
Product (전영훈) YoungHoon Product (전영훈) YoungHoon

Deploying Solar with BentoML

Deploying Solar with BentoML offers a seamless solution for enterprises seeking powerful, cost-efficient large language model (LLM) deployment. Learn how to leverage Solar's compact yet potent 10.7B model with BentoML's deployment capabilities, ensuring optimal performance and scalability. Explore the integration steps and unlock the potential of Solar for your AI initiatives.

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Evalverse: Revolutionizing Large Language Model Evaluation with a Unified, User-Friendly Framework
Tech (전영훈) YoungHoon Tech (전영훈) YoungHoon

Evalverse: Revolutionizing Large Language Model Evaluation with a Unified, User-Friendly Framework

Discover Evalverse: A groundbreaking framework revolutionizing Large Language Model evaluation. With its unified approach and user-friendly features, Evalverse simplifies assessment, making AI advancements inclusive and comprehensive. Explore its key features and architecture, and witness its practical application in our demonstrative video. Join us in driving innovation and accessibility in AI technology with Evalverse!

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Use Case (전영훈) YoungHoon Use Case (전영훈) YoungHoon

Case Study: RAG-based natural language question response

Explore the transformative potential of Retrieval-Augmented Generation (RAG) in revolutionizing information retrieval and response generation. Learn how Upstage's bespoke RAG systems, exemplified by the BIG KINDS AI for news searches, harness advanced AI capabilities and real-time data integration to deliver precise, contextually relevant responses. With a focus on enhancing user experience and mitigating hallucination, Upstage sets a new standard in RAG technology, offering tailored solutions that exceed client expectations.

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Case Study: Client-specific Large Language Model
Use Case (전영훈) YoungHoon Use Case (전영훈) YoungHoon

Case Study: Client-specific Large Language Model

Discover how Upstage addresses the challenges of e-commerce data extraction with a tailored, private Large Language Model (LLM). With a focus on Attribute-Value Extraction (AVE) and sentiment analysis, Upstage's innovative approach streamlines product listing processes and enhances user experience on platforms like Connectwave. Leveraging a Mixture-of-Experts architecture and AWS SageMaker, Upstage sets a new standard in commerce-specific LLM development, driving efficiency and productivity in the e-commerce sector.

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Open Source All About Data Processing, Dataverse
Tech (최유정) Eujeong Tech (최유정) Eujeong

Open Source All About Data Processing, Dataverse

Dataverse is a freely-accessible open-source project designed to streamline the extract, transform, and load (ETL) pipeline using Python. In this post, we delve into the origins of this project and shed light on its future prospects in the realm of open-source data processing.

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