Models

An open-source framework for training language agents with reinforcement learning, letting a developer bring any agent harness and sandbox and switch training backends with one flag.

• Agent frameworks
• Models

A family of pretrained time series forecasting models offering zero-shot univariate, multivariate, and covariate-informed forecasting, deployable through AWS SageMaker or AutoGluon.

• Models

A concise but fully-featured PyTorch transformer implementation bundling many experimental architecture variants and training techniques from published papers.

• Models
• Libraries

A research project applying R1-style reinforcement learning to a vision-language model, reporting better out-of-domain generalization than supervised fine-tuning.

• Models

Open-source infrastructure connecting agent inference, feedback, and learning so an agent's model weights or its prompts, rules, and skills keep improving.

• Agent frameworks
• Models

A collection of Triton kernels for LLM training, from LinkedIn, that reduces GPU memory use and increases training throughput with a one-line change.

• Models

A Python package for generating text with and fine-tuning large language models on Apple silicon using Apple's MLX framework.

• Models
• Inference

A full-stack codebase for training and evaluating draft models used in speculative decoding, covering data preparation, training and benchmark evaluation.

• Models

A family of open-weight language models from Z.ai focused on coding and long-horizon agentic tasks, with GLM-5.3 adding stronger coding and emergent cyber capability.

• Models

A small family of yes/no, multiple-choice and rating decision models, built on Qwen3.5 and Qwen3.8, that can be trained, fine-tuned and served from your own hardware.

• Models

A toolkit for merging pre-trained large language models using an out-of-core approach that can run entirely on CPU or with as little as 8 GB of VRAM.

• Models

A CLI that fine-tunes and post-trains LLMs from a single YAML config and one command, using layer streaming to train an 8B model on a 4 GB laptop GPU.

• Models

EleutherAI's library for training large-scale autoregressive language models on GPUs, built on NVIDIA's Megatron and augmented with DeepSpeed and other optimizations.

• Models

A PyTorch implementation of Reinforcement Learning with Human Feedback (RLHF) on top of the PaLM architecture, aimed at replicating a ChatGPT-style training pipeline in the open.

• Models

An open-source deep research agent optimized for complex research and prediction tasks, scoring highly on the BrowseComp and BrowseComp-ZH benchmarks.

• Models

A PyTorch library that enables accessible large language models through 8-bit and 4-bit quantization, cutting memory use for inference and training.

• Models
• Inference

An LLM post-training framework for reinforcement-learning scaling, connecting Megatron training with SGLang rollout and flexible custom data-generation pipelines.

• Models

An open-weight, 2.8-trillion-parameter multimodal mixture-of-experts model built for long-horizon coding, agentic knowledge work and reasoning, with a one-million-token context window.

• Models

An efficiency-oriented codebase for high-resolution image and video generation with a linear diffusion transformer, covering the SANA, SANA-Video, SANA-Sprint, SANA-WM and Sol-RL family of models with full training and inference pipelines.

• Models
• Generative media

A family of GUI agent models and systems from Tongyi Lab for automating desktop, mobile and browser interfaces, built on GUI-Owl foundation models with tool and MCP calling and long-horizon memory.

• Agent frameworks
• Models

An end-to-end platform for building foundation models: fine-tuning, evaluating and deploying open-weight LLMs such as Qwen, Gemma and Llama, with reinforcement learning, tool use and MCP integration.

• Models
• AI evals

A ChatGPT-like conversational interface powered by RWKV, a fully recurrent (RNN) language model that matches transformer quality while running faster and using less memory.

• Models
• Inference

A high-performance, production-ready open-source RLHF framework built on Ray and vLLM, with a unified agent-based design for scalable reinforcement learning from human feedback.

• Models

A PyTorch implementation of the YOLOv3 real-time object detection model, with training, validation, inference and export to formats such as ONNX, TensorRT and CoreML.

• Models