rLLM (relationLLM) focuses on LLM-based relational data learning, prioritizing: Accuracy, Efficiency, and Economy.

• Accuracy: quality of being true, correct, or exact.
• Efficiency: running time, measured in seconds.
• Economy: money cost, measured in dollars.

• pytorch 2.1.2
• scikit-learn 1.4.0
• llama_cpp_python 0.2.52
• langchain 0.1.8
• langchain-community 0.0.21
• langchain-experimental 0.0.52
• tiktoken 0.6.0
• sentence-transformers 2.3.1
• numpy 1.26.4
• pandas 2.1.4

• We recommmend 4-bit quantized Gemma 2b model, which can be Downloaded from HuggingFace.

• We recommend a light BERT-like model all-MiniLM-L6-v2 to make sentence embedding, which can be obtained directly from HuggingFace.