KDnuggets·2yA Simple to Implement End-to-End Project with HuggingFace
Create an end-to-end project using a pre-trained Hugging Face model for sentiment analysis. This guide details how to deploy the model with FastAPI, build an API endpoint, and use Docker to containerize the application for easy deployment.
Sam Witteveen·2yGemma 2 - Local RAG with Ollama and LangChain
Gemma 2 has been released for multiple formats including Keras, PyTorch, and Hugging Face transformers. This post details the author's experience using the 9B and 27B models in Ollama, highlighting the better performance of the 9B model for real-time responses. A straightforward script is provided to create a fully local Retrieval-Augmented Generation (RAG) system using Gemma 2, Nomic embeddings, and ChromaDB, all executed within VSCode. The steps involve setting up an indexer, embedding transcripts from Alex Hormozi's YouTube channel, and handling text splitting methods. Debugging tips and additional add-ons for the RAG system are also discussed.
GoPenAI·2ySupervised fine tuning (SFT) of Microsoft Phi2 for Text2SQL Task (Part II)
This article discusses the supervised fine-tuning of the Microsoft Phi2 model for the Text2SQL task. It covers data preparation, loading the dataset, preparing input, loading the pre-trained model, setting up a data collator, model training, model evaluation, and concludes with potential areas for improvement.