TranslatedProvides a practical interactive interface for large language models (LLMs) such as GPT/GLM, with special optimization for the paper reading/polishing/writing experience. Modular design, supports custom shortcut buttons & function plugins, supports project analysis & self-translation for Python, C++ and other projects, PDF/LaTeX paper translation & summarization, supports querying multiple LLM models in parallel, and supports local models such as chatglm3. Integrates Tongyi Qianwen (Qwen), deepseekcoder, iFlytek Spark, ERNIE Bot (Wenxin Yiyan), llama2, rwkv, claude2, moss, and more.
TranslatedChatGLM-6B: An Open Bilingual Dialogue Language Model
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced analytics with timeline and execution graph view
- agentneo
- agents
- ai-performance-optimization
- llm-testing
TranslatedChatGLM2-6B: An Open Bilingual Chat LLM
GUI for ChatGPT API and many LLMs. Supports agents, file-based QA, GPT finetuning and query with web search. All with a neat UI.
RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.
TranslatedChatGLM3 series: Open Bilingual Chat LLMs
AI Observability & Evaluation
- llmops
- ai-monitoring
- ai-observability
- llm-eval
BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Management, Observability and more.
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
the LLM vulnerability scanner
PDF GPT allows you to chat with the contents of your PDF file by using GPT capabilities. The most effective open source solution to turn your pdf files in a chatbot!
TranslatedMedicalGPT: Training Your Own Medical GPT Model with ChatGPT Training Pipeline. Training medical large models, implementing incremental pre-training (PT), supervised fine-tuning (SFT), RLHF, DPO, ORPO, and GRPO.
[CVPR2024 Highlight][VideoChatGPT] ChatGPT with video understanding! And many more supported LMs such as miniGPT4, StableLM, and MOSS.
Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. Tracing · Evals · Simulations · Datasets · Gateway · Guardrails. Self-hostable. Apache 2.0.
Steering-first neuron explorer for Qwen3.5-4B: push every MLP neuron, keep every rollout, browse the results
- interpretability
- mechanistic-interpretability
- qwen
- steering
Open decision models from 0.8B to 27B: a calibrated probability for every option in one pass, and a short thought only when unsure. Engine for vLLM, llama.cpp and MLX.
- agents
- calibration
- classification
- decision-making
Turn any LLM into a Jev-style decision model: typed decisions, real probabilities, no training. (continue updating, welcome any issue and PR request)
- calibration
- decision-model
- jev
- jev-model
Real-time monitoring for Claude Code agents through simple hook event tracking.
Trace-native CI/CD for AI agents: grade production traces, cluster failures, freeze them into replayable regression tests, and block PRs that regress. Self-hostable.
Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
- deep-learning
- protein-sequences
- protein-structure
- semi-supervised-learning