4 articles
Master the Hugging Face Transformers library for loading, running, and fine-tuning LLMs — pipelines, tokenizers, generation config, quantization, and integration with the Model Hub. The definitive Python guide.
Learn how to use the Hugging Face Inference API to run LLMs for free without managing infrastructure. This guide covers setup, authentication, model selection, streaming, error handling, and production tips for developers and AI engineers.
Optimize LLM inference speed by 10x. Master quantization tradeoffs, speculative decoding, KV cache management, flash attention, and batching strategies.
Deploy open-source LLMs at scale with vLLM. Compare frameworks, optimize GPU memory, quantize models, and run cost-effective inference in production.