| Before | After | ||
|---|---|---|---|
| 2 | Agentic RAG Cohere on Azure Responsible Use Security Usage Policy Command A Technical Report Command R and Command R+ Model Card Cohere Labs Cohere Labs Acceptable Use Policy More Resources Cohere Toolkit Datasets Improve Cohere Docs DASHBOARD PLAYGROUND DOCS COMMUNITY LOG IN Light On this page Universal Requirements Customer Application Requirements Research Exceptions Scroll to top Responsible Use Usage Policy Copy page (This document was updated on 11/21/2024) Our Usage Policy applies to all Cohere products and services, including Cohere models, software, applications, and application programming interface (collectively “Cohere Services” ). | 2 | Agentic RAG Cohere on Azure Responsible Use Security Usage Policy Command A Technical Report Command R and Command R+ Model Card Cohere Labs Cohere Labs Acceptable Use Policy More Resources Cohere Toolkit Datasets Improve Cohere Docs Introduction Installation Creating a client RAG Reranking Semantic Search Text Generation Tool Use & Agents Transcribing Audio Playground FAQs An Overview of Cohere's Models Cohere Transcribe Aya Aya Vision Aya Expanse Tiny Aya Command A+ Command A Command A Reasoning Command A Translate Command A Vision Command R7B Command R+ Command R Command and Command Lite Embed North Mini Code Rerank Introduction to Text Generation at Cohere Using the Chat API Reasoning Image Inputs Streaming Responses Structured Outputs Parameter Types in Structured Outputs (JSON) Predictable Outputs Advanced Generation Parameters Basic usage End-to-end example Streaming Citations Tool Use Basic usage Usage patterns Parameter types Streaming Citations Tokens and Tokenizers Crafting Effective Prompts Advanced Prompt Engineering Techniques System Messages Create CSV data from JSON data Create a markdown table from raw data Meeting Summarizer Remove PII Add a Docstring to your code Evaluate your LLM response Multilingual interpreter Summarizing Text Safety Modes Introduction to Embeddings at Cohere Semantic Search with Embeddings Multimodal Embeddings Batch Embedding Jobs Rerank Overview Rerank Best Practices API Keys and Rate Limits Going Live Deprecations How Does Cohere's Pricing Work? |
| 3 | Integrating Embedding Models with Other Tools Elasticsearch and Cohere MongoDB and Cohere Redis and Cohere Haystack and Cohere Pinecone and Cohere Weaviate and Cohere Open Search and Cohere Vespa and Cohere Qdrant and Cohere Milvus and Cohere Zilliz and Cohere Chroma and Cohere Cohere and LangChain Chat on LangChain Embed on LangChain Rerank on LangChain Tools on LangChain LlamaIndex and Cohere Overview SDK Compatibility Overview Setting Up Model Deployment Model Deployment - AWS Usage Cohere on AWS Amazon Bedrock Amazon SageMaker Deploy Your Own Finetuned Command-R-0824 Model from AWS Marketplace Cohere on Azure Cohere on Oracle Cloud Infrastructure (OCI) Model Vault Cookbooks LLM University Build Things with Cohere! | ||
| 4 | Cohere Text Generation Tutorial Building a Chatbot with Cohere Semantic Search with Cohere Reranking with Cohere RAG with Cohere Building an Agent with Cohere Agentic RAG Routing Queries to Data Sources Generating Parallel Queries Performing Tasks Sequentially Generating Multi-Faceted Queries Querying Structured Data (Tables) Querying Structured Data (SQL) Cohere on Azure Text Generation Semantic Search Reranking Retrieval Augmented Generation (RAG) Tool Use & Agents Usage Policy Command R and Command R+ Model Card Cohere Labs Acceptable Use Policy Cohere Toolkit Datasets Improve Cohere Docs API Keys Versioning Model Commands Admin Commands Finetune Generate Docs Model Admin Auth Config Key Ping Usage User Deployment Options Amazon Bedrock Amazon SageMaker Oracle Cloud Infrastructure (OCI) Private Deployment Fine-tuning on AWS Fine-tuning Cohere Models on Amazon Bedrock Fine-tuning Cohere Models on Amazon SageMaker Cohere SDKs Errors and Warnings Amazon SageMaker and Cohere Appendix 2: Building Apps Module 7: The Cohere Platform Sandbox App Examples Deploying with Amazon SageMaker Semantic Search A Deeper Dive Into Semantic Search Text Embeddings Evaluation Methods for Search Fine-Tuning for Rerank Multilingual Semantic Search With Cohere and Langchain Chaining Prompts Fine-tuning a Generative Model Prompt Engineering Prompting Command R Using Command R7B on Hugging Face Using Command A on Hugging Face Conclusion Text Summarization Cohere's Command Model The Generate Endpoint Use Case Ideation What is Generative AI? | ||
| 5 | Classification Models Classification Using Embeddings The Classify Endpoint Clustering Using Embeddings The Embed Endpoint Visualizing Data Classification Evaluation Metrics Fine-tuning an Embedding Model for Classification Semantic Search Using Embeddings Setting up Applications Conclusion - The Cohere Platform Endpoints Foundational Models Serving Platform Classification Models BAK MEOR Creating Custom Generative Models Structure of the Course (WITH DEPLOYMENT ADDED) Backup Structure [ALT] The Generate Endpoint Customer Support Intent Recognition Sentiment Analysis Toxicity Detection Using the Embed API Multilingual Embed Models Introduction to Cohere Embeddings Cross-Lingual Content Moderation Customer Feedback Aggregation Multilingual Semantic Search Supported Languages Documents and Citations Sending Feedback Book an appointment Single-step vs Multi-step Semantic Search Fine-tuning for Generate Starting the Generate Fine-tuning Understanding the Generate Fine-tuning Results Improving the Generate Fine-tuning results Temperature Top-k & Top-p Introduction Fine-tuning with the Web-UI Programmatic Fine-tuning Fine-tuning for Chat Preparing the Chat Fine-tuning Data Starting the Chat Fine-Tuning Understanding the Chat Fine-tuning Results Improving the Chat Fine-tuning Results Fine-tuning for Rerank Preparing the Rerank Fine-tuning Data Starting the Rerank Fine-Tuning Understanding the Rerank Fine-tuning Results Improving the Rerank Fine-tuning Results Fine-tuning for Classify Preparing the Classify Fine-tuning data Train and deploy a fine-tuned model Understanding the Classify Fine-tuning Results Improving the Classify Fine-tuning Results FAQs / Troubleshooting DASHBOARD PLAYGROUND DOCS COMMUNITY LOG IN Light On this page Universal Requirements Customer Application Requirements Research Exceptions Scroll to top Responsible Use Usage Policy Copy page (This document was updated on 11/21/2024) Our Usage Policy applies to all Cohere products and services, including Cohere models, software, applications, and application programming interface (collectively “Cohere Services” ). | ||
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