How to Use Huggingface Models in Google Colab (in 3 minutes)

🎓 Tutorial: Running Hugging Face Models in Google Colab | Text Generation with Gemma 3B

In this video, I’ll walk you through how to run a Hugging Face language model directly in Google Colab using the transformers library. We’ll use the unsloth/gemma-3-1b-it model to generate text from a custom prompt — all running on a free GPU provided by Colab!

🚀 What You’ll Learn:
How to use the pipeline() function from the Hugging Face transformers library

How to load and run a large language model (LLM) for text generation

The purpose of key parameters like max_length, do_sample, truncation, and device

How to understand and handle typical runtime warnings

Best practices for experimenting with language models in a Colab environment

🧠 Who This Video Is For:
Beginners in Natural Language Processing (NLP) and machine learning

Students, researchers, or developers working with LLMs

Anyone interested in testing Hugging Face models without local installation

💡 Code used in this tutorial is included in the video.
Use it as a foundation to explore other NLP tasks like summarization, translation, or sentiment analysis.

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#huggingface #googlecolab #textgeneration #Gemma3B #transformers #llm #pythonai #machinelearning #nlp