Loading...
Loading...
XTuring: Build, personalize and control your own LLMs. It is listed under Development & Code on AI Registry as a free tool.
The tools below are approved listings in the same category, ordered by how closely their tags match XTuring. This is an automatic list. We have not written a researched verdict for XTuring yet, so treat it as a shortlist and check each vendor's pricing page before switching.
Built from each tool's listing. Vendors can update their own listing after claiming it.
Train and serve LLMs at extreme speed and massive throughput.
Surogate is a platform for designing, deploying and monitoring autonomous AI agents without writing code. An agent is assembled from a model, knowledge bases built from documents, sites and repositories, tools including any MCP server, skills and guardrails, then deployed as a managed cloud service that keeps working a...
Synthetic data curation for post-training and structured data extraction
Bespoke Curator is an open source Python library from Bespoke Labs for building synthetic data pipelines. It is used to generate and curate data for post training language models and to extract structured information from unstructured inputs, with the library handling the orchestration of large numbers of model calls. ...
DataDreamer: Prompt. Generate Synthetic Data.
DataDreamer is an open source Python library for prompting, synthetic data generation and model training workflows. Its authors describe it as simple, efficient and research grade. A single Python script can load a large language model, generate a synthetic dataset from an instruction, transform that dataset with furth...
FASHN VTON v1.5: Efficient Maskless Virtual Try-On in Pixel Space
FASHN VTON v1.5 is an open weights virtual try on model from FASHN AI. Given an image of a person and an image of a garment, it generates a photorealistic result showing the garment worn, working directly on RGB pixels rather than in a compressed latent space and without requiring a segmentation mask of the body. Both ...
Easiest and laziest way for building multi-agent LLMs applications.
LazyLLM is an open source development framework for building and optimizing multi agent AI applications. It is written in Python and aims to cover the stages of application development in one toolkit: application construction, data preparation, model deployment, model fine tuning and evaluation. The stated goal is to l...
Streamlining reinforcement learning with RLOps.
AgileRL builds tools for training specialized AI agents with reinforcement learning. Its main product, Arena, is an enterprise platform that turns a company's raw data and workflows into training environments and LLM datasets, then trains, tunes and deploys a small model that becomes an expert at that specific task ins...