Directory
Models and machine learning covers model hubs, research papers, training guides and evaluation tools. The topic mixes practical resources with reference material, so you will find repositories that host downloadable models next to sites that explain how a technique works. Some entries are collections of papers or benchmarks, and others are tutorials that walk through fine-tuning or deployment. It pays to compare the model licence, the training data, the hardware needed and the date of the last update. The field moves quickly, so verify version notes on the source before you build on anything listed here.
Odysseus is a self-hosted AI workspace for running language models on one's own hardware. It offers chat, autonomous agents, tools and MCP connections, model serving, an email assistant, deep research, model comparison and persistent memory. The project is described as local-first and privacy-first, with no telemetry.
Sarvam provides machine-learning models, research, training resources, or evaluation tools.
G4F Chat is a conversational AI platform that supports private, customizable conversations using multiple AI providers and models. It includes features such as cloud sync, conversation export, markdown rendering, speech recognition, voice synthesis, custom system prompt configuration and MCP server support.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Arena is a platform that allows users to interact with multiple open source and proprietary frontier AI models in a single interface for research, coding and creative tasks. It includes a model leaderboard feature, and notes that inputs are processed by third-party AI, so responses may be inaccurate.
Unsloth Studio is an open-source, no-code web UI for training, running and exporting open models in one local interface. It supports GGUF, MLX and diffusion image/video models on Mac, Windows and Linux, and runs AI models offline without a GPU. A graphical Data Recipes workflow creates synthetic datasets from uploaded files.
LLM Papers provides machine-learning models, research, training resources, or evaluation tools.
Direct is a chat tool for interacting with multiple frontier AI models. It allows prompting several open source and proprietary large language models in one place, for research, coding, and creative tasks.
Rate Display is an AI tool or resource for chat, research, automation, media generation, or model development.
Solar is a browser-based playground from Upstage Console that lets users test Solar LLM and Document AI tools. It supports features including AI chat, document parsing, OCR, and question answering over user-uploaded files.
Call Annie is a web guide or update reference covering changes, screenshots, notices, or community notes.
r/Ishchat points to a Reddit community or thread with discussion, updates, troubleshooting, or shared resources.
Telegram link is a Telegram channel, group, or bot link for updates, files, community posts, or support.
ModelScope Finetuning supports machine learning models, deployment, inspection, datasets, or AI development workflows.
Apertus provides conversational AI for questions, tasks, and general assistance.
Meituan Long Cat provides machine-learning models, research, training resources, or evaluation tools.
Mistral Studio helps build, test, automate, or manage AI agents, prompts, models, and API workflows.
Netron is a viewer for neural network, deep learning and machine learning models. It supports formats including ONNX, TensorFlow Lite, PyTorch, TensorFlow, Core ML, OpenVINO, Keras, Caffe, Darknet, Safetensors and NumPy. It is available as a browser version and installers for macOS, Linux and Windows, plus a Python package. Experimental support exists for MLIR, JAX, GGUF and other formats.
Documentation for Fine Tuning Guide, covering setup, features, and practical usage.
r/Bard points to a Reddit community or thread with discussion, updates, troubleshooting, or shared resources.
AnythingLLM is an all-in-one AI application for chatting with documents, using AI agents, and connecting local or cloud LLMs. It includes a built-in local LLM engine, vector databases, document pipelines, multi-user support, and a no-code agent builder. It is distributed under an MIT license.
r/ClaudeAI points to a Reddit community or thread with discussion, updates, troubleshooting, or shared resources.
Awesome LLM Resources is a GitHub-hosted curated list of resources for applied AI engineering. The collection is marked as a work in progress and aggregates relevant materials for applied AI engineering work.
Fcoijmefliggikpeofhojmkpoooocifk provides machine-learning models, research, training resources, or evaluation tools.
