Collaborative and hybrid recommendation systems
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Updated
Jun 2, 2024 - Jupyter Notebook
Collaborative and hybrid recommendation systems
PEFT is a wonderful tool that enables training a very large model in a low resource environment. Quantization and PEFT will enable widespread adoption of LLM.
Llama2-Medical-Chatbot is a medical chatbot that uses the Llama-2-7B-Chat-GGML model and the pdf The Gale Encyclopedia of Medicine, Volume 1, 2nd Edition. It is still under development, but it has the potential to be a valuable tool for patients, healthcare professionals, and researchers.
The Llama-2-GGML-CSV-Chatbot is a conversational tool leveraging the powerful Llama-2 7B language model. It facilitates multi-turn interactions based on uploaded CSV data, allowing users to engage in seamless conversations.
Collecting data for Building Lucknow's first LLM
This project has implemented the RAG function on Jetson and supports TXT and PDF document formats. It uses MLC for 4-bit quantization of the Llama2-7b model, utilizes ChromaDB as the vector database, and connects these features with Lama_Index. I hope you like this project.
taxGPT take home assignment
MUICT Chatbot: Source code for the ITCS498 Special Topic in Computer Science project at Faculty of ICT, Mahidol University
A holistic way of understanding how LLaMA and its components run in practice, with code and detailed documentation.
🌟 A UI based LLM tool, having integrated large language models
Kickstart with LLMs
Professor Codephreak local language model pursuit of agency. Upgrades are occurring in this repo, the original codephreak is historically stored at https://github.com/Professor-Codephreak/automind/
Locally run Lllama2 GUI interface using Python tkinter library
Fine tuning LLM model (part of Hyperverge Nexus program)
An LLM enabled XML generator for Indian laws in the LegalDocML and LegalRuleML formats
IntelliCodeEx is a code explanation tool powered by LLM (Language Model) that utilizes the open-source Llama-2 7B GGML quantized model. It's designed to provide intelligent explanations for various programming languages.
Unleash the full potential of exascale LLMs on consumer-class GPUs, proven by extensive benchmarks, with no long-term adjustments and minimal learning curve.
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