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The SEAL LLM Leaderboard is a resource from Scale Labs that provides expert-driven benchmarks and updated rankings for large language models. It evaluates capabilities including agentic coding, frontier reasoning, and safety alignment, with over 20 benchmarks and assessments of more than 100 models from leading AI labs and open-source contributors.
SEAL LLM Leaderboards provides machine-learning models, research, training resources, or evaluation tools.
SillyTavern is a locally installed user interface for interacting with text generation LLMs, image generation engines and TTS voice models. It began in February 2023 as a fork of TavernAI 1.2.8 and is built around character cards, collections of prompts that set the behavior of the LLM. It is free and open-sourced.
SpeechMap.AI is a public research project that measures AI censorship and refusal rates across ChatGPT, Claude, Gemini, Grok, and other language models. It records refusal rates for each model release and publishes a free-speech leaderboard tracking changes over time.
StreamingLLM is a technique from researchers at Meta AI, MIT and Carnegie Mellon University that extends a language model's context to millions of tokens without large compute or memory resources. The article describes it as addressing the fixed context length of models such as Llama-2, which has a context of approximately 4,000 tokens.
Text Generation Inference is a toolkit for deploying and serving large language models, implemented as a Rust, Python and gRPC server. It supports models including Llama, Falcon, StarCoder, BLOOM and GPT-NeoX, with features such as token streaming, continuous batching and quantization. The repository is archived, read-only, and in maintenance mode, with pull requests limited to minor bug fixes and maintenance.
A visualisation of major large-language models ranked by performance using the MMLU benchmark, which consists of 16,000 multiple-choice questions across 57 academic subjects. It also presents selected lawsuits filed against AI companies and notes that MMLU has some critiques.
TorchText provides models, data loaders and abstractions for language processing, powered by PyTorch. The library includes dataset iterators, basic NLP building blocks, text-processing transformations, pre-trained models and vocabulary classes. The repository was archived by its owner on Sep 10, 2025, and is now read-only; development is stopped with 0.18 the last stable release.
Vals AI provides machine-learning models, research, training resources, or evaluation tools.
VBench is a Hugging Face Space created by Vchitect that hosts a leaderboard for AI video generation models. Users can upload a zip file with their model's evaluation JSON files and provide details such as model name, link, team, and contact email. The application extracts the metrics and updates the benchmark leaderboard accordingly.
VoxelBench provides machine-learning models, research, training resources, or evaluation tools.
Weights & Biases is an open-source AI developer platform. It is used to train and fine-tune machine learning models, and manage models across the full lifecycle from experimentation to production. The associated wandb library is hosted in a public GitHub repository.
Repository of Ultralytics YOLO models, including YOLO27, YOLO26, YOLO11, and YOLOv8, covering object detection, instance segmentation, semantic segmentation, image classification, pose estimation, and object tracking. Models can be installed as the ultralytics package, used through a CLI yolo command or Python, and exported to formats such as ONNX.
A Hugging Face blog post introducing Matryoshka Embedding models. It explains embeddings as numerical representations and describes how Matryoshka models store more important information in earlier dimensions, allowing large embeddings to be truncated while remaining useful. It covers theoretical training and training with Sentence Transformers, with a comparison to a regular embedding model.
Google Speech Gen helps build, test, automate, or manage AI agents, prompts, models, and API workflows.
Creates, rewrites or summarizes written content with language models.
Creates or edits images with generative models and visual controls.
A simple guide to fine-tuning Llama 2 Brev docs provides machine-learning models, research, training resources, or evaluation tools.
Ability AI provides machine-learning models, research, training resources, or evaluation tools.
A library created for PyTorch users to launch, train, and use PyTorch models on almost any device and distributed configuration. It abstracts the boilerplate code related to multi-GPUs, TPUs, and fp16 while leaving the rest of the code unchanged, and supports automatic mixed precision and FSDP and DeepSpeed.
Accord.MachineLearning is a NuGet package, part of the Accord.NET Framework, that contains Support Vector Machines, Decision Trees, Naive Bayesian models, K-means, Gaussian Mixture models, and general algorithms such as Ransac, Cross-validation and Grid-Search for machine-learning applications. Version 3.8.0 targets .NET Standard 1.4 and .NET Framework 3.5.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Adept AI provides machine-learning models, research, training resources, or evaluation tools.
