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Building Agents with Hugging Face Transformers: Building, Fine-Tuning, Scaling, and Bridging LLMs with Transformer-Powered Agents
Paperback
Publisher: Independently Published
Published: Aug 4 2025
Pages: 322
Weight: 1.23
Height: 0.67 Width: 7.00 Depth: 10.00
Language: English
This hands-on, code-driven guide unlocks the power of building intelligent AI agents using Hugging Face Transformers and related tools. Whether you're a machine learning engineer, AI researcher, or advanced developer, this book equips you with the knowledge and practical skills to create, fine-tune, scale, and deploy transformer-powered agents for real-world applications, from task automation to multi-agent systems.
What You'll Learn:
- The complete process of building AI agents, from task-oriented automation to autonomous research systems, using Hugging Face's ecosystem.
- How to integrate large language models (LLMs) like Zephyr, Mistral, and Qwen with tools, APIs, and code execution for tasks such as scheduling, data processing, and content generation.
- Techniques for fine-tuning agents with efficient methods like LoRA and PEFT, enabling customization on consumer-grade hardware.
- Designing collaborative and competitive multi-agent systems, with frameworks like LangChain, smolagents, and PettingZoo for complex workflows.
- Observability and monitoring practices, including logging, visualization, and benchmarking against standards like HumanEval and GAIA.
- Deployment strategies using Hugging Face Inference Endpoints, FastAPI, Docker, and Kubernetes for scalable, production-ready agents.
- Ethical considerations, including bias mitigation, privacy protection, and safe constraints for autonomous agents.
- Emerging trends like continual learning, multi-modal agents (integrating vision and audio), and advanced reasoning algorithms.
Built for Advanced Practitioners:
This book is designed for those ready to move beyond basic LLM prompting and build sophisticated, production-grade agents. It's not for beginners, it's for practitioners who want to create robust, scalable, and ethical AI systems using open-source tools.
Who Should Read This Book?
- Machine learning engineers building task-oriented or autonomous agents.
- AI developers creating enterprise solutions for automation, research, or multi-agent collaboration.
- Researchers exploring advanced planning, reasoning, or multi-modal agent capabilities.
- Advanced programmers leveraging Hugging Face Transformers for custom AI workflows.
- Anyone developing intelligent agents for industries like logistics, healthcare, or customer support.
Tools Covered:
- Hugging Face Transformers, Datasets, smolagents, and Inference Endpoints.
- LangChain, LangGraph, and LlamaIndex for agent orchestration and workflows.
- PyTorch for fine-tuning and model optimization.
- PettingZoo and MATE for multi-agent environments.
- Docker, Kubernetes, FastAPI, and Redis for deployment and scaling.
- Prometheus, Grafana, and logging tools for observability.
- Ethical tools like TextBlob and safety libraries for responsible AI.
If you're ready to harness the full potential of Hugging Face Transformers to build intelligent, scalable, and ethical AI agents, this is your definitive guide. Packed with real-world projects, complete code templates, and practical insights, it's time to transform your ideas into production-ready agents.
Get your copy now and start building the future of intelligent systems.
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