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Classification-Text (148 results) showing 1 - 20
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ByCohere | Ver v3.3.12
Embed translates text and images into numerical vectors that models can understand. The most advanced generative AI apps rely on high-performing embedding models to understand the nuances of user inputs, search results, and documents. This Embed model has 1024 dimensions. | |
ByCohere | Ver v2.0.1 At Cohere, we are committed to breaking down barriers and expanding access to cutting-edge NLP technologies that power projects across the globe. By making our innovative multilingual language models available to all developers, we continue to move toward our goal of empowering developers,... | |
ByCohere | Ver v3.3.13
Embed 3 translates text and images into numerical vectors that models can understand. The most advanced generative AI apps rely on high-performing embedding models to understand the nuances of user inputs, search results, and documents. This Embed model has 1024 dimensions. This version is also a... | |
ByCohere | Ver v3.3.12
Embed Light translates text and images into numerical vectors that models can understand. The most advanced generative AI apps rely on high-performing embedding models to understand the nuances of user inputs, search results, and documents. Embed Light is a smaller version of Embed with 384... | |
ByVoyage AI | Ver v1.0.1
Text embedding models are neural networks that transform texts into numerical vectors. They are a crucial building block for semantic search/retrieval systems and retrieval-augmented generation (RAG) and are responsible for the retrieval quality. voyage-large-2 is a cutting-edge embedding model... | |
ByJina AI | Ver 1.3 jina-embeddings-v3 is a multilingual multi-task text embedding model designed for a variety of NLP applications. Based on the Jina-XLM-RoBERTa architecture, this model supports Rotary Position Embeddings to handle long input sequences up to 8192 tokens. Additionally, it features 5 LoRA adapters to... | |
ByVoyage AI | Ver v1.0.1
Text embedding models are neural networks that transform texts into numerical vectors. They are a crucial building block for semantic search/retrieval systems and retrieval-augmented generation (RAG) and are responsible for the retrieval quality. voyage-code-2 is optimized for retrieving code and... | |
ByJina AI | Ver 3.2 Jina Embeddings v2 Base model is optimized for highly accurate embeddings - For speed of inference and memory efficiency use the Small model. jina-embeddings-v2-base-en is an open-source English embedding model supporting 8192 sequence length. This state-of-the-art AI embedding model enables many a... | |
ByVoyage AI | Ver v1.0.1
Multimodal embedding models are neural networks that transform multiple modalities, such as text and images, into numerical vectors. They are a crucial building block for semantic search/retrieval systems and retrieval-augmented generation (RAG) and are responsible for the retrieval quality.... | |
ByVoyage AI | Ver v1.0.0
Text embedding models are neural networks that transform texts into numerical vectors. They are a crucial building block for semantic search/retrieval systems and retrieval-augmented generation (RAG) and are responsible for the retrieval quality. voyage-3-large is a state-of-the-art... | |
ByVoyage AI | Ver v1.0.0
Text embedding models are neural networks that transform texts into numerical vectors. They are a crucial building block for semantic search/retrieval systems and retrieval-augmented generation (RAG) and are responsible for the retrieval quality. voyage-3 is a general-purpose embedding that: [1]... | |
Snowflake enables every organization to mobilize their data with the Data Cloud. Customers use the Data Cloud to unite siloed data, discover and securely share data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single data experience that spans multiple... | |
ByVoyage AI | Ver v1
Text embedding models are neural networks that transform texts into numerical vectors. They are a crucial building block for semantic search/retrieval systems and retrieval-augmented generation (RAG) and are responsible for the retrieval quality. voyage-2 is a cutting-edge embedding model trained... | |
ByVoyage AI | Ver v1
Text embedding models are neural networks that transform texts into numerical vectors. They are a crucial building block for semantic search/retrieval systems and retrieval-augmented generation (RAG) and are responsible for the retrieval quality. voyage-law-2 is an embedding model optimized for... | |
ByVoyage AI | Ver v1
Text embedding models are neural networks that transform texts into numerical vectors. They are a crucial building block for semantic search/retrieval systems and retrieval-augmented generation (RAG) and are responsible for the retrieval quality. voyage-multilingual-2 is optimized for multilingual... | |
ByObjectways Technologies | Ver 1.0 Starting from $500.00/hr or from $10,000.00/yr (100% savings) for software + AWS usage fees Jupyter notebook that allows users to annotate a searchable PDF. Settings are configurable. Supports multi-page PDF as well. | |
ByDatasaur | Ver 6.79.0 Datasaur is a comprehensive data labeling and extraction platform for Natural Language Processing (NLP). Datasaur helps machine learning teams better manage their labeling workforce and improve the quality of their training data. Our best-in-class software comes with ML-assisted labeling and workfo... | |
ByCohere | Ver v3.3.12
Embed Light translates text and images into numerical vectors that models can understand. The most advanced generative AI apps rely on high-performing embedding models to understand the nuances of user inputs, search results, and documents. Embed Light is a smaller version of Embed with 384... | |
ByJina AI | Ver 1.0 jina-colbert-v2 is an open-source multilingual ColBERT-style embedding model supporting 8192 sequence length. This model produces vectors of size 128 for tokens in input documents. ColBERT (Contextualized Late Interaction over BERT) leverages the deep language understanding of BERT while introdu... | |
ByLexisNexis | Ver Version 1 Legal taxonomy classification is an important "first step" needed in legal text processing. You need to know what category of Law the legal text is referring to. Many Lawyers rely on the Legal Taxonomy provided by the LexisNexis application. This Sagemaker model isolates that taxonomy... |