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Guides

Learn about Cohere's UI in the playground overview. Read Intro to Large Language Models with Cohere for a brief visual overview to Large Language Models (LLMs) and some of their applications.

Text Classification#

Text classification is one of the most useful applications of Large Language Models (LLMs). They can classify text using a small number of examples (few-shot classification).

See the text classification with Classify tutorial which demonstrates the Classify endpoint.

See the text classification with Embeddings tutorial which demonstrates the Embed endpoint.

Text Generation#

LLMs can write coherent text like no other human technology before them could. This can be used for creative copy, but also for summarization and paraphrasing. We tune the inputs using prompt engineering techniques that get the model to produce useful outputs. Important text generations parameters include top-k and top-p.

Semantic Search#

Learn how to use embeddings to build semantic search capabilities.

Finetuning#

Customize Cohere models to fit your use case by finetuning our baseline models with your own data. Learn about finetuning generation models in addition to finetuning representation models.

Entity Extraction#

Extract information from text using only a few examples.

Model Evaluation#

Learn how the Likelihood endpoint can be a useful tool for model evaluation.

Notebooks and code examples#

See the notebooks repo for code examples on common LLM use cases.

Integrations#

The Cohere platform is often used in pipelines alongside other tools and services.