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Published directory entries matching your search.
Harbor is a CLI and companion app that starts a pre-wired local LLM stack. Users pick services such as Ollama, llama.cpp, vLLM, Open WebUI, SearXNG, Speaches and ComfyUI, and Harbor handles Docker Compose orchestration, configuration and cross-service connectivity with a single harbor up command.
A blog guide on FinetuneDB covering best practices for evaluating Large Language Model outputs. It explains what LLM output evaluation is, why it matters, and describes evaluation datasets, model-based judgments and human judgments as approaches for structuring the process.
A free LLM course from Hugging Face that teaches large language models and natural language processing. It covers the Transformers, Datasets, Tokenizers, and Accelerate libraries and the Hugging Face Hub, along with some libraries outside the ecosystem. The course is without ads.
Indic LLM Arena provides machine-learning models, research, training resources, or evaluation tools.
An archived educational course repository for learning about LLMs, LLMOps and vector databases by designing, training and deploying a real-time financial advisor LLM system. It includes source code, video and reading materials, and covers a training pipeline using QLoRA and a streaming pipeline ingesting financial news. The repository was archived by its owner and is read-only.
Respan is an AI gateway that routes requests to over 1,000 models through one API endpoint, with automatic fallbacks, response caching, and spending limits. It also provides built-in observability for tracing LLM calls, tool calls, and agent steps, plus automated evaluations and security testing for masking PII and red-teaming agents before launch.
LangKit is an open-source toolkit for monitoring large language models (LLMs). It extracts signals from LLM prompts and responses, and offers features such as text quality assessment, relevance metrics, and sentiment analysis to support LLM observability.
A Python framework for building LLM-powered applications through a multi-agent paradigm. Developers set up agents, equip them with optional components such as LLMs, vector stores and tools, assign tasks, and have them exchange messages to solve problems. It works with practically any LLM and does not use LangChain.
Libera.Chat is an IRC network for collaboration on free and open source software projects. Its site publishes a bot and LLM policy update, addressing unsupervised LLM-driven bots on the network and announcing planned policy additions for 2026-05-30. It also provides a frequently asked questions guide covering accounts, channels, bans and staff contact.
A Challenging, Contamination-Free LLM Benchmark.
LLama Cpp Agent is a framework designed for easy interaction with large language models (LLMs). It allows users to chat with LLMs, execute structured function calls, and retrieve structured output. It works with models not fine-tuned for JSON output or function calls. The project is hosted as a public repository on GitHub.
LLM App is an open-source project providing ready-to-run cloud templates for retrieval-augmented generation (RAG), AI pipelines and enterprise search with live data. It is Docker-friendly and designed to stay synchronized with data sources including Sharepoint, Google Drive, S3, Kafka, PostgreSQL and real-time data APIs, hosted by pathwaycom on GitHub.
No-code batch compute platform for LLM evaluation and tuning workloads.
LLM Explorer is a directory of open-source language models and AI agents. It lists 150 AI agents and 64,811 open-source large and small language models, grouped into categories with benchmarks and analytics.
LLM Papers provides machine-learning models, research, training resources, or evaluation tools.
LLM pricing calculator is a web page for estimating model costs per million tokens. It takes input, cached input and output token counts and reports cost per million input tokens, per million cached input tokens and per million output tokens. It notes that direct token-based price comparisons may not be entirely accurate because different models use different tokenizers.
LLM Resources Hub provides machine-learning models, research, training resources, or evaluation tools.
LLMStack is a no-code platform for building generative AI apps, chatbots and agents using imported data. It supports major model providers and lets users share apps publicly or restrict access with roles.
LLM Stats is an AI leaderboard that ranks GPT, Claude, Gemini, Llama, DeepSeek and more than 300 AI models by intelligence, speed and price. Scores are computed from public benchmarks and live API metrics.
A free downloadable guide from Kolena Inc. on testing large language models. It identifies principles for creating reliable testing protocols and details approaches for measuring model effectiveness in NLP tasks such as text summarization and prompt engineering, and discusses tracking performance differences over time.
A self-hosted proxy providing OpenAI and Anthropic compatible API endpoints for multiple LLM providers, so existing applications can use any supported provider through a single API key. It includes a FastAPI proxy application and a reusable Python resilience library for API key management, rotation, and failover.
LLMKube is a Kubernetes operator for self-hosted large language model inference across heterogeneous GPU fleets supporting NVIDIA CUDA, AMD Vulkan, and Apple Silicon Metal. It supports runtimes including llama.cpp, vLLM, TGI, and mlx-server, offers multi-GPU sharding, model caching, and OpenAI-compatible endpoints. It is licensed under Apache-2.0 and designed for homelab and on-prem fleet deployment, and is actively developed.
LLMs Bullshit Benchmark provides machine-learning models, research, training resources, or evaluation tools.
Lunary is an observability and prompt management platform for LLM-based applications. It provides chatbot analytics, agent tracing, prompt templates, topic classification, PII masking and feedback tracking. A self-hostable option is offered. The Team cloud plan costs $20 per user per month, billed monthly, and payment is required to activate a workspace.
