Hugging Face Transformers
Definition pending
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Practical example
Hugging Face Transformers is THE Python library for loading, fine-tuning, and running transformer models. It provides a unified API for 100,000+ models from the Hugging Face Hub. model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-3B") loads the model in one line. The library handles tokenization, generation, and training.
Workflow example
Production pattern: (1) develop and fine-tune using Transformers + PEFT in Python, (2) export to GGUF for llama.cpp/ollama deployment (using convert-hf-to-gguf.py), or (3) serve directly with Transformers + vLLM for GPU serving. The Transformers library is great for development but not optimized for production throughput — always benchmark Transformers vs llama.cpp/vLLM before deploying. For CPU serving, ONNX Runtime often beats Transformers.