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

Huggingface Workshop

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.

Pick a dataset to learn from from Datasets.

Explore the dataset and prepare it for training.

Pick a model to learn from the chosen data from 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. Training notebook for this application: https://colab.research.google.com/drive/1mC1b5KkkGJRcqtaRH09Qb25NZelCGnIZ?usp=sharing

Deploy the model with 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 :)


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