#
Starred repositories
47
stars
written in Jupyter Notebook
Clear filter
🦜🔗 Build context-aware reasoning applications
A programming framework for agentic AI 🤖
A guidance language for controlling large language models.
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
🦖 𝗟𝗲𝗮𝗿𝗻 about 𝗟𝗟𝗠𝘀, 𝗟𝗟𝗠𝗢𝗽𝘀, and 𝘃𝗲𝗰𝘁𝗼𝗿 𝗗𝗕𝘀 for free by designing, training, and deploying a real-time financial advisor LLM system ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 𝘷𝘪𝘥𝘦𝘰 & 𝘳𝘦𝘢𝘥𝘪𝘯𝘨 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭𝘴
A high performance implementation of HDBSCAN clustering.
Jupyter Notebooks to help you get hands-on with Pinecone vector databases
Neo4j graph construction from unstructured data using LLMs
Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
The Open Source Memory Layer For Autonomous Agents
Convert any text to a graph of knowledge. This can be used for Graph Augmented Generation or Knowledge Graph based QnA
Developer APIs to Accelerate LLM Projects
Jupyter notebooks that support my graph data science blog posts at https://bratanic-tomaz.medium.com/
Multiple NVIDIA GPUs or Apple Silicon for Large Language Model Inference?
Using GPT to organize and access information, and generate questions. Long term goal is to make an agent-like research assistant.
Evaluate the accuracy of LLM generated outputs
Generative Representational Instruction Tuning
Generative AI on AWS
code and resources used in the Going Meta sessions
This repository provides an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses sophisticated graph based algorithm to handle the tasks.
Build, evaluate and observe LLM apps
Graph based retrieval + GenAI = Better RAG in production
Implementation on how to use Kolmogorov-Arnold Networks (KANs) for classification and regression tasks.
🐳 | Dockerfiles for the RunPod container images used for our official templates.
Simple introduction to LLM Agents