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Total Size:
68.9 MB
Info Hash:
230DD69DC960B625854D6C5959FD3DA2EFD5E9C7
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Added:
Oct. 22, 2025, 9:04 a.m.
Stats:
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(Last updated: Oct. 22, 2025, 9:05 a.m.)
| File | Size |
|---|---|
| Lee W. Hugging Face in Action 2025.pdf | 68.9 MB |
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68.9 MB
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34]
2025-10-22
| Uploaded by andryold1 | Size 68.9 MB | Health [ 26 /34 ] | Added 2025-10-22 |
NOTE
SOURCE: Lee W. Hugging Face in Action 2025
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COVER
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MEDIAINFO
Textbook in PDF format Everything you need to know about using the tools, libraries, and models at Hugging Face—from transformers, to RAG, LangChain, and Gradio. Hugging Face in Action reveals how to get the absolute best out of everything Hugging Face, from accessing state-of-the-art models to building intuitive frontends for AI apps. With Hugging Face in Action you’ll learn: Utilizing Hugging Face Transformers and Pipelines for NLP tasks Applying Hugging Face techniques for Computer Vision projects Manipulating Hugging Face Datasets for efficient data handling Training Machine Learning models with AutoTrain functionality Implementing AI agents for autonomous task execution Developing LLM-based applications using LangChain and LlamaIndex Constructing LangChain applications visually with LangFlow Creating web-based user interfaces using Gradio Building locally running LLM-based applications with GPT4ALL Querying local data using Large Language Models Want a cutting edge transformer library? Hugging Face’s open source offering is best in class. Need somewhere to host your models? Hugging Face Spaces has you covered. Do your users need an intuitive frontend for your AI app? Hugging Face’s Gradio library makes it easy to build UI using the Python skills you already have. In Hugging Face in Action you’ll learn how to take full advantage of all of Hugging Face’s amazing features to quickly and reliably prototype and productionize AI applications
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