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Learn how fine-tuning tool-calling language models helps AI systems use specific tools to perform real-world tasks more effectively.
This article explains how to fine-tune the Qwen3 language model using Low-Rank Adaptation (LoRA) and NVIDIA NeMo AutoModel in a single-GPU Google Colab environment, focusing on parameter-efficient training techniques and automated workflows.
Perplexity has released pplx-embed, a new collection of multilingual embedding models optimized for large-scale retrieval tasks. The models feature bidirectional attention and diffusion-based training, enhancing their performance in web-scale applications.
