# Fireworks AI Docs

## Docs

- [Custom SSO](https://docs.fireworks.ai/accounts/sso): Set up custom Single Sign-On (SSO) authentication for Fireworks AI
- [Managing users](https://docs.fireworks.ai/accounts/users): Add and delete additional users in your Fireworks account
- [Align transcription](https://docs.fireworks.ai/api-reference/audio-alignments)
- [Transcribe audio (realtime)](https://docs.fireworks.ai/api-reference/audio-realtime-transcriptions)
- [Transcribe audio](https://docs.fireworks.ai/api-reference/audio-transcriptions)
- [Translate audio](https://docs.fireworks.ai/api-reference/audio-translations)
- [Create Dataset](https://docs.fireworks.ai/api-reference/create-dataset)
- [Create Deployed Model](https://docs.fireworks.ai/api-reference/create-deployed-model)
- [Create Deployment](https://docs.fireworks.ai/api-reference/create-deployment)
- [Create Fine-tuning Job](https://docs.fireworks.ai/api-reference/create-fine-tuning-job)
- [Create Model](https://docs.fireworks.ai/api-reference/create-model)
- [Create User](https://docs.fireworks.ai/api-reference/create-user)
- [null](https://docs.fireworks.ai/api-reference/creates-an-embedding-vector-representing-the-input-text)
- [Delete Dataset](https://docs.fireworks.ai/api-reference/delete-dataset)
- [Delete Deployed Model](https://docs.fireworks.ai/api-reference/delete-deployed-model)
- [Delete Deployment](https://docs.fireworks.ai/api-reference/delete-deployment)
- [Delete Fine-tuning Job](https://docs.fireworks.ai/api-reference/delete-fine-tuning-job)
- [Delete Model](https://docs.fireworks.ai/api-reference/delete-model)
- [Generate an image](https://docs.fireworks.ai/api-reference/generate-a-new-image-from-a-text-prompt)
- [Get Account](https://docs.fireworks.ai/api-reference/get-account)
- [Get Dataset](https://docs.fireworks.ai/api-reference/get-dataset)
- [Get Dataset Upload Endpoint](https://docs.fireworks.ai/api-reference/get-dataset-upload-endpoint)
- [Get Deployment](https://docs.fireworks.ai/api-reference/get-deployment)
- [Get Fine-tuning Job](https://docs.fireworks.ai/api-reference/get-fine-tuning-job)
- [Get Model](https://docs.fireworks.ai/api-reference/get-model)
- [Get Model Download Endpoint](https://docs.fireworks.ai/api-reference/get-model-download-endpoint)
- [Get Model Upload Endpoint](https://docs.fireworks.ai/api-reference/get-model-upload-endpoint)
- [Get User](https://docs.fireworks.ai/api-reference/get-user)
- [Introduction](https://docs.fireworks.ai/api-reference/introduction)
- [List Datasets](https://docs.fireworks.ai/api-reference/list-datasets)
- [List Deployments](https://docs.fireworks.ai/api-reference/list-deployments)
- [List Fine-tuning Jobs](https://docs.fireworks.ai/api-reference/list-fine-tuning-jobs)
- [List Models](https://docs.fireworks.ai/api-reference/list-models)
- [List Users](https://docs.fireworks.ai/api-reference/list-users)
- [null](https://docs.fireworks.ai/api-reference/post-chatcompletions)
- [null](https://docs.fireworks.ai/api-reference/post-completions)
- [Update Dataset](https://docs.fireworks.ai/api-reference/update-dataset)
- [Update Deployment](https://docs.fireworks.ai/api-reference/update-deployment)
- [Update Fine-tuning Job](https://docs.fireworks.ai/api-reference/update-fine-tuning-job)
- [Update Model](https://docs.fireworks.ai/api-reference/update-model)
- [Update User](https://docs.fireworks.ai/api-reference/update-user)
- [Upload Dataset Files](https://docs.fireworks.ai/api-reference/upload-dataset-files): Provides a streamlined way to upload a dataset file in a single API request. This path can handle file sizes up to 150Mb. For larger file sizes use [Get Dataset Upload Endpoint](get-dataset-upload-endpoint).

- [Validate Dataset Upload](https://docs.fireworks.ai/api-reference/validate-dataset-upload)
- [Validate Model Upload](https://docs.fireworks.ai/api-reference/validate-model-upload)
- [Start here](https://docs.fireworks.ai/cookbook/cookbook_landing)
- [Build with Fireworks](https://docs.fireworks.ai/cookbook/learn_with_fireworks/ecosystem_examples): Step-by-step guides for hands-on exploration, ideal for interactive learning of AI techniques.
- [Community showcase](https://docs.fireworks.ai/cookbook/projects_showcase/community_examples): Creative user-contributed projects that showcase innovative applications of Fireworks in diverse contexts.
- [Regions](https://docs.fireworks.ai/deployments/regions): Fireworks runs a global fleet of hardware on which you can deploy your models.
- [Reserved capacity](https://docs.fireworks.ai/deployments/reservations)
- [Account setup & management](https://docs.fireworks.ai/faq/account/access/setup-management): Solutions for common account access issues and management procedures for Fireworks.ai accounts
- [Billing management](https://docs.fireworks.ai/faq/billing-pricing-usage/billing/billing-management): Information about Fireworks.ai invoicing and API billing.
- [Credit system](https://docs.fireworks.ai/faq/billing-pricing-usage/billing/credit-system): Understanding how Fireworks.ai billing, credits, and account suspension work.
- [Cost structure](https://docs.fireworks.ai/faq/billing-pricing-usage/pricing/cost-structure): Understanding Fireworks.ai pricing and fees for various services.
- [Discounts](https://docs.fireworks.ai/faq/billing-pricing-usage/pricing/discounts): Information about bulk usage discounts and special pricing options.
- [Billing & scaling](https://docs.fireworks.ai/faq/deployment/ondemand/billing-scaling): Understanding billing and scaling mechanisms for on-demand deployments.
- [Deployment issues](https://docs.fireworks.ai/faq/deployment/ondemand/deployment-issues): Troubleshooting and resolving common issues with on-demand deployments.
- [Hardware options](https://docs.fireworks.ai/faq/deployment/ondemand/hardware-options): Understanding hardware choices for Fireworks.ai on-demand deployments.
- [On-demand deployment scaling](https://docs.fireworks.ai/faq/deployment/ondemand/ondemand-deployment-scaling): Understanding Fireworks.ai system scaling and request handling capabilities.
- [Performance optimization](https://docs.fireworks.ai/faq/deployment/performance/optimization): Guidelines for optimizing performance and benchmarking Fireworks.ai deployments.
- [Costs & management](https://docs.fireworks.ai/faq/deployment/serverless/costs-management): Understanding costs and model availability for serverless deployments.
- [Performance issues](https://docs.fireworks.ai/faq/deployment/serverless/performance-issues): Troubleshooting timeout errors and performance issues with serverless LLM models.
- [Service levels](https://docs.fireworks.ai/faq/deployment/serverless/service-levels): Understanding SLAs and service guarantees for Fireworks.ai serverless deployments.
- [Certifications](https://docs.fireworks.ai/faq/enterprise/compliance/certifications): Information about Fireworks.ai compliance certifications and HIPAA requirements.
- [Enterprise quotas](https://docs.fireworks.ai/faq/enterprise/service/quotas): Understanding quota allocations for Enterprise customers.
- [Platform support](https://docs.fireworks.ai/faq/general/support/platform-support): Information about Fireworks.ai deployment regions, general support channels, and platform requests.
- [Support structure & access](https://docs.fireworks.ai/faq/general/support/structure-access): Information about Fireworks.ai support options, access methods, and communication channels.
- [Enterprise support tiers & SLAs](https://docs.fireworks.ai/faq/general/support/tiers-slas): Detailed information about Fireworks.ai support priority levels and response time commitments.
- [Platform models](https://docs.fireworks.ai/faq/models/availability/platform-models): Information about custom and available models on Fireworks.ai.
- [Fine-tuning service](https://docs.fireworks.ai/faq/models/fine-tuning/service-overview): Overview of Fireworks.ai fine-tuning capabilities and supported models.
- [Fine-tuning troubleshooting](https://docs.fireworks.ai/faq/models/fine-tuning/troubleshooting): Solutions for common fine-tuning deployment and access issues.
- [FLUX capabilities](https://docs.fireworks.ai/faq/models/image-generation/flux): Understanding FLUX image generation features and limitations.
- [Limitations & controls](https://docs.fireworks.ai/faq/models/inference/limitations-controls): Understanding model limitations, safety features, and token limits.
- [Inference performance](https://docs.fireworks.ai/faq/models/inference/performance): Understanding model performance, quantization, and batching capabilities.
- [Data security](https://docs.fireworks.ai/faq/security/infrastructure/data-security): Information about Fireworks.ai data encryption and security measures.
- [Security documentation](https://docs.fireworks.ai/faq/security/infrastructure/documentation): Access to Fireworks.ai security policies and documentation.
- [Model security](https://docs.fireworks.ai/faq/security/infrastructure/model-security): Understanding model security and guardrail implementations.
- [Private access](https://docs.fireworks.ai/faq/security/network/private-access): Understanding private connection options for Fireworks.ai services.
- [Fine-tuning models](https://docs.fireworks.ai/fine-tuning/fine-tuning-models)
- [Fine-tuning models via API](https://docs.fireworks.ai/fine-tuning/fine-tuning-via-api)
- [Concepts](https://docs.fireworks.ai/getting-started/concepts): This document outlines basic Fireworks AI concepts.
- [Introduction](https://docs.fireworks.ai/getting-started/introduction): Fireworks AI is a generative AI inference platform to run and customize models with industry-leading speed and production-readiness.
- [Quickstart](https://docs.fireworks.ai/getting-started/quickstart): Get started in 5 minutes
- [Using function-calling](https://docs.fireworks.ai/guides/function-calling)
- [On-demand deployments](https://docs.fireworks.ai/guides/ondemand-deployments): Deploying on your own GPUs
- [Prompt caching](https://docs.fireworks.ai/guides/prompt-caching)
- [Querying embedding models](https://docs.fireworks.ai/guides/querying-embeddings-models)
- [Querying text models](https://docs.fireworks.ai/guides/querying-text-models)
- [Querying vision-language models](https://docs.fireworks.ai/guides/querying-vision-language-models)
- [Deploying models](https://docs.fireworks.ai/models/deploying)
- [Overview](https://docs.fireworks.ai/models/overview)
- [null](https://docs.fireworks.ai/models/quantization)
- [Uploading a custom model](https://docs.fireworks.ai/models/uploading-custom-models)
- [Using grammar mode](https://docs.fireworks.ai/structured-responses/structured-output-grammar-based)
- [Using JSON mode](https://docs.fireworks.ai/structured-responses/structured-response-formatting)
- [Authentication](https://docs.fireworks.ai/tools-sdks/firectl/commands/authentication): Authentication for access to your account
- [Create a Dataset](https://docs.fireworks.ai/tools-sdks/firectl/commands/create-dataset): Create a Dataset on Fireworks AI platform
- [Create a deployment](https://docs.fireworks.ai/tools-sdks/firectl/commands/create-deployment): Create a Deployment on Fireworks AI platform
- [Create a fine-tuning job](https://docs.fireworks.ai/tools-sdks/firectl/commands/create-finetune-job): Create a fine-tuning job with a base model
- [Create Model](https://docs.fireworks.ai/tools-sdks/firectl/commands/create-model): Create a model on Fireworks AI platform
- [Delete Resources](https://docs.fireworks.ai/tools-sdks/firectl/commands/delete-model): Deletes resource(s) in a Fireworks AI account
- [Deploy Model](https://docs.fireworks.ai/tools-sdks/firectl/commands/deploy-model): Deploy a model on Fireworks AI platform
- [Download a model](https://docs.fireworks.ai/tools-sdks/firectl/commands/download-model): Download a model from third-party locations
- [Get Resources](https://docs.fireworks.ai/tools-sdks/firectl/commands/get-model): Retrieves model information from Fireworks AI platform
- [Import Model](https://docs.fireworks.ai/tools-sdks/firectl/commands/import-model): Imports specified model from Fireworks AI Platform
- [List Resources](https://docs.fireworks.ai/tools-sdks/firectl/commands/list-models): List various resources in an Fireworks AI account
- [Undeploy Model](https://docs.fireworks.ai/tools-sdks/firectl/commands/undeploy-model): Undeploy a model on Fireworks AI platform
- [Update Resources](https://docs.fireworks.ai/tools-sdks/firectl/commands/update): Updates Resources on Fireworks AI platform
- [Getting Started](https://docs.fireworks.ai/tools-sdks/firectl/firectl): Learn to create, deploy, and manage resources using Firectl
- [OpenAI compatibility](https://docs.fireworks.ai/tools-sdks/openai-compatibility)
- [API Reference](https://docs.fireworks.ai/tools-sdks/python-client/api-reference)
- [Getting Started](https://docs.fireworks.ai/tools-sdks/python-client/installation)
- [Inference errors](https://docs.fireworks.ai/troubleshooting/status_error_codes/inference_error_code): This page lists common error codes encountered during inference requests using the Fireworks API, their meanings, and potential resolutions.


## Optional

- [Community](https://discord.gg/fireworks-ai)
- [Blog](https://fireworks.ai/blog)