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Enhancing the facility of Llama 2
Massive Language Fashions (LLMs) are right here to remain. With the latest launch of Llama 2, open-source LLMs are approaching the efficiency of ChatGPT and with correct tuning may even exceed it.
Utilizing these LLMs is usually not as easy because it appears particularly if you wish to fine-tune the LLM to your particular use case.
On this article, we’ll undergo 3 of the most typical strategies for bettering the efficiency of any LLM:
- Immediate Engineering
- Retrieval Augmented Technology (RAG)
- Parameter Environment friendly Nice-Tuning (PEFT)
There are numerous extra strategies however these are the best and can lead to main enhancements with out a lot work.
These 3 strategies begin from the least advanced technique, the so-called low-hanging fruits, to one of many extra advanced strategies for bettering your LLM.
To get essentially the most out of LLMs, you possibly can even mix all three strategies!
Earlier than we get began, here’s a extra in-depth overview of the strategies for simpler reference:
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