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Tune and Deploy LoRA LLMs with NVIDIA TensorRT-LLM NVIDIA Technical Blog
microsoft LoRA: Code for loralib, an implementation of “LoRA: Low-Rank Adaptation of Large Language Models” One challenge in deploying LLMs is how to efficiently serve hundreds or thousands of tuned models. For example, a single base LLM, such as Llama 2, may have many LoRA-tuned variants per language or locale. A standard system would require…
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fkodom lora-pytorch: Simple but robust implementation of LoRA for PyTorch Compatible with NLP, CV, and other model types. Strongly typed and tested.
2106 09685 LoRA: Low-Rank Adaptation of Large Language Models This article explores LoRA’s principles, architecture, and impact on language model adaptation. Click the numbers below to download the RoBERTa and DeBERTa LoRA checkpoints. If LoRA has a separate lm_head and embedding, these will replace the lm_head and embedding of the base model. To optimize a…