【用LoRA微调LLM的实用技巧】《Practical Tips for Finetuning LLMs Using LoRA (Low-Rank Adaptation)》 http://t.cn/A6W32jXt #机器学习#
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Hands-on LoRa: Practical Fine-tuning LLMs using LoRaDeep Learning is an experimental science. If your hands aren't dirty, how can your mind be nifty?Introduction: "LoRA, which freezes the pretrained model weights and injects trainable rank decomposition matrices into each layer of the ...
Fine-Tuning a 7B Model in a single 16GB GPU using QLoRA. We are going to see a brief introduction to quantization, used to reduce the size of big Large Language Models. With quantization, you can load big models reducing the memory resources needed. It also applies to the fine-tuning pr...
Fine-Tuning a 7B Model in a single 16GB GPU using QLoRA. We are going to see a brief introduction to quantization, used to reduce the size of big Large Language Models. With quantization, you can load big models reducing the memory resources needed. It also applies to the fine-tuning pr...
Fine-Tuning a 7B Model in a single 16GB GPU using QLoRA. We are going to see a brief introduction to quantization, used to reduce the size of big Large Language Models. With quantization, you can load big models reducing the memory resources needed. It also applies to the fine-tuning pr...
Fine-Tuning a 7B Model in a single 16GB GPU using QLoRA. We are going to see a brief introduction to quantization, used to reduce the size of big Large Language Models. With quantization, you can load big models reducing the memory resources needed. It also applies to the fine-tuning pr...