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The iOS and OS X neural network framework.
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Brainstorm is a GitHub repository for a neural network library developed by IDSIA. It is designed to be fast, flexible, and fun for neural network development, with documentation and support resources available for users implementing the library.
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Bread Dataset Viewer is a VS Code extension for viewing and handling large datasets. It opens JSONL, Parquet, CSV, TSV, JSON, and Arrow/Feather files by streaming and lazy-loading data, and provides Cards, Table, and Raw views. It includes 16 production LLM tokenizers from GPT, Claude, Llama, and Qwen for chat completion data.
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Breeze is a numerical processing library for Scala.
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brexhq/prompt-engineering is a GitHub repository containing Brex's Prompt Engineering Guide. It provides tips and tricks for working with Large Language Models such as OpenAI's GPT-4, with content covering the definition of large language models, an incomplete history of language models, and the concept of prompts.
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Theano based library for deep and recurrent neural networks.
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A curated GitHub list of papers and tools covering LLM threats and vulnerabilities from a security and privacy standpoint. It includes paper summaries, key takeaway points, citations in a bib file, and frameworks and taxonomies such as OWASP Top 10 for LLM Applications.
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Brood Box is a command-line tool for running coding agents inside hardware-isolated microVMs. It boots a microVM via libkrun and KVM, mounts a copy-on-write snapshot of the workspace, and allows review of each file change before it is accepted. The project is described as experimental, with APIs and behavior subject to change between releases.
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Distributed decision tree ensemble learning in Scala.
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BudgetML is a tool for deploying a machine learning inference service to a secured HTTPS API endpoint with less than 10 lines of code. It runs the model on a Google Cloud Platform preemptible instance, generates a FastAPI server endpoint, and provides interactive Swagger docs. The project states that the library is not being actively maintained.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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burn is a next-generation tensor library and deep learning framework developed by tracel-ai. It is designed to prioritize flexibility, efficiency, and portability, with available resources covering use with Rust, its ecosystem, supported backends, and training and inference functionality.
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Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
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The official repo for “Dolphin: Document Image Parsing via Heterogeneous Anchor Prompting”, ACL, 2025.
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ByteHub is an open-source tool designed to simplify the creation and management of feature stores. It is maintained as a public repository on GitHub under the bytehub-ai organization, with documentation and tutorials available for users.
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Caffe is a deep learning framework developed by Berkeley AI Research and community contributors, designed with expression, speed, and modularity in mind. It is released under the BSD 2-Clause license and includes associated reference models.
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CAJAL is a local scientific paper generator that runs entirely on the user's machine, connecting a local Ollama or LLM backend without hosted API calls. It produces seven-section papers from a research idea using an Ollama-compatible model.
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Authors:, Dexter Storey, Ted Spare.
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CAMEL is an open-source community and framework for studying multi-agent systems at scale. It implements and supports various agents, tasks, prompts, models and simulated environments, and describes design principles including evolvability, scalability, statefulness and code-as-prompt.
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Role-playing approach for LLMs and auto-agents like BabyAGI & AutoGPT.
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Collection of stable diffusion webui colab for different checkpoints.
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Candle is a minimalist machine learning framework for Rust with a focus on performance, including GPU support, and ease of use. It provides examples and online browser demos for models such as whisper, LLaMA2, T5, yolo and Segment Anything.
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Model interpretability and understanding library for PyTorch.
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A general classifier module to allow Bayesian and other types of classifications.