What can an AI teammate do with Hugging Face?

A Hugging Face AI assistant can search and browse the model hub, run inference against hosted models, retrieve dataset and model metadata, and list Spaces. It can automate model evaluation, surface recommendations, and integrate open-source AI into scheduled workflows. Write actions like running inference require your approval.

Which models can my teammate run inference on?

Your teammate can call any model available through the Hugging Face Inference API, including text generation, summarization, translation, classification, and embedding models. Model availability depends on your Hugging Face account tier.

Is inference output stored anywhere?

Inference results are processed during task execution and saved only as part of your run output. Raw inputs and outputs are not stored separately beyond your run history.

How is a Hugging Face AI teammate different from running the Inference API directly?

Calling the API directly requires writing code for every request. A Hugging Face AI teammate reasons about which model to use, chains multiple calls together, compares outputs, and delivers a summary - all on a schedule or triggered by another workflow, without any manual scripting.

Developer tools

AI Teammate for Hugging Face

An AI teammate that runs inference, manages models, and automates ML workflows on Hugging Face.

Your AI teammate for Hugging Face runs model inference, searches the model hub, lists datasets, and retrieves model metadata. A capable AI assistant for automating ML experimentation, monitoring model repositories, and integrating open-source AI into your workflows. Write actions always require your approval.

Hugging Face hosts hundreds of thousands of models, but finding the right one and running it consistently takes time. A Hugging Face AI teammate searches the hub, runs inference, and surfaces results so you can iterate on ideas without leaving your workflow.

Connect Hugging Face Visit Hugging Face

What your AI teammate can do with Hugging Face

Read-only actions run automatically. Write actions require your approval.

Read-only actions

list models

Browse models on the hub filtered by task, library, or author

search models

Find models by name, tag, or task type across the full hub

get model info

Fetch metadata, tags, and README content for a specific model

list datasets

Browse available datasets by task, language, or author

search datasets

Find datasets by name or tag across the hub

list spaces

Browse Hugging Face Spaces demos by task or framework

Write actions (require approval)

run inference

Run a prompt or input through any hosted model via the Inference API

Example workflows with Hugging Face

Real tasks you can run on a schedule or on demand.

task

run weekly inference benchmarks across candidate models and post results to Slack

task

search the hub for the best open-source model for a new task and summarize the top options

task

monitor a model repository for new versions and notify the team when updates are released

task

pull dataset metadata and generate a data card summary for internal documentation

How to connect Hugging Face

Create a free m8tes account.

Connect Hugging Face

Click Connect and complete the OAuth flow or enter your API key.

Create a task

Give your AI teammate a task that uses Hugging Face. It handles the rest.

Hugging Face AI teammate: FAQ

Common questions about using an AI teammate with Hugging Face.

Build an AI teammate for Hugging Face

Connect Hugging Face to an autonomous AI teammate that reads data, runs tasks on schedule, and delivers structured output.

AI teammates — all integrations
Build a teammate that uses Hugging Face alongside your other tools.

Related integrations

Teams that use Hugging Face also connect these.

OpenAI

Developer tools

Anthropic

Developer tools

Replicate

Developer tools

GitHub

Developer tools

Start using Hugging Face today

Free to start. No credit card required.

Start free