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dataloaders
dataloaders PublicDataloaders is a versatile library designed for processing and formatting datasets to support various Retrieval-Augmented Generation (RAG) pipelines, facilitating efficient evaluation and analysis.
Python 3
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rag-pipelines
rag-pipelines PublicAdvanced RAG Pipelines and Evaluation: Self-Reflective RAG, Corrective RAG, Adaptive RAG, Sub-Query Generation and Routing, DSPy, DeepEval
Python 3
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hyperparameter-tuning
hyperparameter-tuning PublicEffect of Optimizer Selection and Hyperparameter Tuning on Training Efficiency and LLM Performance
Python 2
Repositories
- dataloaders Public
Dataloaders is a versatile library designed for processing and formatting datasets to support various Retrieval-Augmented Generation (RAG) pipelines, facilitating efficient evaluation and analysis.
- rag-pipelines Public
Advanced RAG Pipelines and Evaluation: Self-Reflective RAG, Corrective RAG, Adaptive RAG, Sub-Query Generation and Routing, DSPy, DeepEval
- llm-finetuning Public
- vectordb Public
Created pipelines for Semantic Search, Metadata Filtering, Hybrid Search, Reranking, and Retrieval-Augmented Generation (RAG) for the TriviaQA, ARC, PopQA, FactScore, and Edgar datasets. These pipelines have been implemented for the Pinecone, Weaviate, Milvus, Qdrant and Chroma vector databases.
- hyperparameter-tuning Public
Effect of Optimizer Selection and Hyperparameter Tuning on Training Efficiency and LLM Performance
- finbert-hf Public