This repository provides code examples and Jupyter notebooks for the Cohere Platform, targeting developers and researchers looking to integrate Cohere's natural language processing capabilities into their applications. It serves as a practical guide to leveraging Cohere's APIs for various NLP tasks.

How It Works

The notebooks demonstrate practical applications of Cohere's models through interactive code examples. They cover common NLP use cases such as text generation, summarization, classification, and embeddings, showcasing how to interact with the Cohere API using Python.

Quick Start & Requirements

• Primary install / run command: pip install cohere
• Prerequisites: Python 3.7+, Cohere API key.
• Official Docs: https://docs.cohere.com/
• Notebooks: https://github.com/cohere-ai/cohere-developer-experience/tree/main/notebooks

Highlighted Details

• Demonstrates generation, classification, summarization, and embeddings.
• Provides examples for fine-tuning models.
• Includes use cases for RAG (Retrieval-Augmented Generation).

Maintenance & Community

This repository is part of the broader Cohere developer experience efforts. For community engagement, refer to Cohere's official channels.

Licensing & Compatibility

The code examples are typically provided under a permissive license, allowing for broad use and integration. Specific licensing details should be confirmed within the repository or associated documentation.

Limitations & Caveats

The notebooks are examples and may require adaptation for specific production environments or advanced use cases. They are dependent on the availability and current versions of the Cohere API.