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8 articles
Learn to build a simple AI chatbot using Python and Hugging Face Transformers, understanding both the technical implementation and consumer concerns around AI adoption.
Learn how NVIDIA's TensorRT Model Connect streamlines AI model deployment by converting Hugging Face checkpoints to optimized TensorRT engines in two commands, eliminating intermediate steps and enabling native C++ inference.
Learn to analyze EdgeBench AI agent benchmarking data by downloading datasets, parsing task specifications, and examining performance metrics across different task categories and execution settings.
Learn how to work with transformer architectures using Python and Hugging Face's transformers library. This tutorial teaches you to load models, process text, and understand the core components of modern AI systems like Google's Gemini.
Learn how to fine-tune a pre-trained language model using Hugging Face's Transformers library, a technique used by AI companies like DeepSeek.
Learn how to efficiently explore the TaskTrove dataset using streaming parsing with Python and Hugging Face's datasets library.
Learn how to install and use Meta's NeuralSet package to analyze neuroscientific data with AI techniques, including fMRI, M/EEG, and HuggingFace embeddings.
Learn to build and deploy a chatbot using Hugging Face Transformers and Gradio, gaining hands-on experience with the core technologies behind AI systems like Alibaba's Qwen.