voyage-01
In the ever-evolving landscape of artificial intelligence, Voyage AI introduces the Voyage-01 model, a state-of-the-art text embedding solution engineered to redefine retrieval-augmented generation (RAG) applications. This groundbreaking model is designed to set new standards in performance, efficiency, and domain specificity. Unparalleled Performance The Voyage-01 model outshines OpenAI's latest
voyage-ai
The landscape of machine learning models is constantly evolving, and Voyage AI's latest offering, the voyage/voyage-large-2, is setting a new standard in text embedding. This model is designed for a range of applications, from summarization and classification to highly effective retrieval tasks, making it a versatile tool
voyage-finance-2
The financial sector is a data-intensive industry where precision and accuracy are paramount. To address these unique demands, Voyage AI has developed the voyage-finance-2, a domain-specific embedding model tailored for financial data retrieval and retrieval-augmented generation (RAG). Unmatched Performance Voyage-finance-2 has undergone rigorous evaluation across 11 different finance retrieval datasets,
voyage-ai
The landscape of embedding models is rapidly evolving, and Voyage AI's latest release, voyage-code-3, is setting new benchmarks in code retrieval performance and cost-efficiency. This model stands out by offering free output pricing and a highly competitive input price of just $0.18 per 1M tokens, catering to
voyage-ai
In the ever-evolving landscape of AI-powered search technologies, Voyage AI has launched two groundbreaking models: rerank-2 and rerank-2-lite. These models promise to redefine the efficiency and accuracy of search result ranking, setting new standards in the industry. Unmatched Performance and Accuracy The rerank-2 model enhances accuracy over OpenAI’s text-embedding-3-large
voyage-2
The world of AI continues to evolve, offering more sophisticated tools tailored to meet diverse needs. One such innovation is the Voyage-2, a state-of-the-art text embedding model by Voyage AI. Designed with efficiency in mind, this model promises to balance cost, latency, and retrieval quality effectively. Voyage-2 is a general-purpose
ai
In the ever-evolving landscape of artificial intelligence, the Voyage-law-2 model emerges as a beacon of innovation for the legal sector. Developed by Voyage AI Innovations Inc., this cutting-edge text embedding model is specifically designed to enhance semantic retrieval of legal texts, setting a new standard in the realm of legal
voyage-ai
The voyage-lite-02-instruct model is an advanced text embedding solution offered by Voyage AI, specifically designed to excel in tasks like classification, clustering, and sentence textual similarity. This instruction-tuned model brings a unique set of features tailored for these specialized applications. Model Overview The voyage-lite-02-instruct model offers a generous context length
voyage-multimodal-3
In the rapidly evolving landscape of artificial intelligence, the introduction of advanced models often leads to transformative shifts in how we handle complex data. One such groundbreaking development is the Voyage-Multimodal-3, a cutting-edge multimodal embedding model designed to seamlessly integrate and process interleaved text and images. Voyage-Multimodal-3 stands out by
ai
In the rapidly evolving landscape of artificial intelligence, Voyage AI has unveiled its latest embedding models, Voyage 3 and Voyage 3-lite. These models redefine retrieval quality, latency, and cost efficiency, setting a new standard in the realm of AI-driven data processing. Overview of Models Voyage 3 and its lighter counterpart,
voyage-ai
The world of AI is constantly evolving, and Voyage AI is at the forefront with its innovative models designed to meet diverse needs. Among its offerings, the voyage/voyage-lite-01 stands out as an efficient embedding model, providing a cost-effective solution for various applications. Model Overview The voyage/voyage-lite-01 is part
llm
The Bedrock/Meta-Textgeneration-Llama-2-7B is a cutting-edge Large Language Model (LLM) developed by Meta as part of the Llama 2 series. This series ranges from 7 billion to 70 billion parameters, with the 7B model offering a balance of size and capability. Its development involved Supervised Fine-Tuning (SFT) and Reinforcement Learning