DeepKE VS llama_farm

Scaling language models have revolutionized widespread NLP tasks, yet little comprehensively explored few-shot relation extraction with large language models. In this paper, we investigate principal methodologies, in-context learning and data generation, for few-shot relation extraction via GPT-3.5 through exhaustive experiments. To enhance few-shot performance, we further propose task-related instructions and schema-constrained data generation. We observe that in-context learning can achieve performance on par with previous prompt learning approaches, and data generation with the large language model can boost previous solutions to obtain new state-of-the-art few-shot results on four widely-studied relation extraction datasets. We hope our work can inspire future research for the capabilities of large language models in few-shot relation extraction. Code is available in \url{https://github.com/zjunlp/DeepKE/tree/main/example/llm.

I do i recursively https://github.com/atisharma/llama_farm/blob/main/llama_farm/summaries.hy

It's funny that you asked that and then someone posted an app that's almost entirely Hy language. I'm just sharing it so you have one example:

https://github.com/atisharma/llama_farm/tree/main

The AI's have limited ability to either handle large documents or track conversations. This tool is an attempt to solve that problem. It works with OpenAI and open-source AI's.

Then you might like https://github.com/atisharma/llama_farm

I use this

Bark and another one I forgot. See this for example implementation.

This is what I use

It's now incorporated in llama-farm.