---
title: Huggingface Workshop
emoji: 😻
colorFrom: yellow
colorTo: gray
sdk: streamlit
sdk_version: 1.41.1
app_file: app.py
pinned: false
---
# Huggingface Workshop

write this as an instructor

steps during the workshop:
- show huggingface; as a website and as a company
- define how huggingface can be valuable in daily business?!

should take 

Huggingface has become an essential hub for the artifical intelligence community to share models, datasets and intelligent applications.

Discover it with us.

Decide on an AI usecase.
- describe what to do
e.g. 5 examples

Pick a dataset to learn from from [Datasets](https://huggingface.co/datasets).

what do I do in ml life-cycle

Explore the dataset and prepare it for training.

Pick a model to learn from the chosen data from [Models](https://huggingface.co/models). To save time choose a pre-trained model that you want to refine for the specific usecase.

Train the model.

Use GoogleColab to train a model on GPU for free.

Deploy the model with [Spaces](https://huggingface.co/spaces) and build an interface so that the model's behavior can be tested. Using spaces you can run your model on minimal but often sufficient hardware for free.

Done :)



Stuck? Take a look at the [hints](https://huggingface.co/spaces/till-onethousand/huggingface-workshop/blob/main/HINTS.md).

---

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference