Concepts
This document outlines basic Fireworks AI concepts.
Resources
Account
Your account is the top-level resource under which other resources are located. Quotas and billing are enforced at the account level, so usage for all users in an account contribute to the same quotas and bill.
For developer accounts, the account ID is auto-generated from the email address used to sign up. Enterprise accounts can optionally choose a custom, unique account ID.
User
A user is an email address associated with an account. Users added to an account have full access to delete, edit, and create resources within the account, such as deployments and models.
Model
A model is a set of model weights and metadata associated with the model. A model cannot be used for inference until it is deployed to one or more deployments, creating a “deployed model”. There are two types of models:
- Base models
- Parameter-efficient fine-tuned (PEFT) addons
See our Models overview page for details.
Deployment
A deployment is a collection (one or more) model servers that host one base model and optionally one or more PEFT addons (also known as LoRA adapters).
Fireworks provides a set of “serverless” deployments that host common base models. These deployments may be used for serverless inference as well as hosting serverless addons.
Deployed model
A deployed model is an instance of a base model or PEFT addon that is loaded into a deployment.
Dataset
A dataset is an immutable set of training examples that can be used to fine-tune a model.
Fine-tuning job
A fine-tuning job is an offline training job that uses a dataset to train a PEFT addon model.
Resource names and IDs
A full resource name looks like
The individual segments my-account
and my-model
are account and model IDs, respectively.
Resource IDs must satisfy the following constraints:
- between 1 and 63 characters (inclusive)
- consist of a-z, 0-9, and hyphen (-)
- does not begin or end with a hyphen (-)
Some APIs take the full resource name, while others may take a resource ID if the context is clear.
Control plane and data plane
The Fireworks API can be split into a control plane and a data plane.
- The control plane consists of APIs used for managing the lifecycle of resources. This includes your account, models, and deployments.
- The data plane consists of the APIs used for inference and the backend services that power them.
Interfaces
Users can interact with Fireworks through one of many interfaces:
- The web console at https://fireworks.ai
- The command-line interface
firectl
- Python SDK
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