The main features of roboflow/inference are: Model Serving & Deployment.
Open-source alternatives to roboflow/inference include: paddlepaddle/lark — LARK is a development toolkit for training, fine-tuning, and deploying large language models and multimodal models… huggingface/notebooks — This is a collection of Jupyter notebooks that serve as educational guides for training, fine-tuning, and deploying… pytorch/tutorials — The PyTorch Tutorials repository is a collection of educational resources that provides step-by-step guidance on… autogluon/autogluon — AutoGluon is an automated machine learning framework and multimodal library designed to automate the end-to-end… bentoml/bentoml — BentoML is a machine learning model serving framework and GPU-accelerated inference server designed to package,… alexsjones/llmfit.
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LARK is a development toolkit for training, fine-tuning, and deploying large language models and multimodal models based on PaddlePaddle. It functions as a comprehensive framework that includes an LLM training orchestrator, an inference server, and a multimodal model framework for processing text, image, and video inputs. The project features a retrieval-augmented generation system for building conversational applications that integrate web search and private knowledge bases. It provides specific capabilities for multimodal reasoning and complex logic, enabling the extraction of structured da
AutoGluon is an automated machine learning framework and multimodal library designed to automate the end-to-end pipeline from data preprocessing to high-accuracy model training and validation. It functions as an automated model trainer for tabular, image, text, and time series data, as well as a tool for time series forecasting and foundation model finetuning. The project is distinguished by its ability to jointly process and fuse different data types, allowing for the construction of multimodal neural networks that integrate images, text, and structured tables. It supports zero-shot inferenc
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