Hugging Face Exploration: NLP, Image Generation, and Speech Recognition

This collection of Jupyter notebooks showcases various use cases using Hugging Face's popular libraries and models. From natural language processing (NLP) tasks to text-to-image generation and speech recognition, these examples are perfect for exploring Hugging Face’s powerful tools like transformers.

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Key Notebooks Include:

• Hugging Face Pipeline: Explore sentiment analysis, named entity recognition, and more.

• Fine-Tuning Models: Learn how to fine-tune pre-trained models for sentiment analysis and resume training from checkpoints.

• Stable Diffusion: Generate images from text prompts using advanced models.

• Speech Recognition: Convert spoken language into text using OpenAI's Whisper model.

 

For the code and detailed explanations, click below to access the repository. You can also open the notebooks directly in Google Colab using the links in the README.md.