The Segment Anything Model (SAM) is a powerful tool that allows users to segment any object in an image with just a few clicks. This makes it a great tool for a variety of tasks, such as object detection, tracking, and editing. SAM is also very easy to use, making it a great option for both beginners and experienced users.

Awesome-LLMOps is a curated list of the best LLMOps tools, providing a comprehensive collection of frameworks and tools for building, deploying, and managing large language models (LLMs) and AI agents. The repository includes a wide range of tools for tasks such as building multimodal AI agents, fine-tuning models, orchestrating applications, evaluating models, and serving models for inference. It covers various aspects of the machine learning operations (MLOps) lifecycle, from training to deployment and observability. The tools listed in this repository cater to the needs of developers, data scientists, and machine learning engineers working with large language models and AI applications.

Koko-aio shader is an all-in-one CRT shader tool that can be configured with various parameters to run on different GPUs. It aims to provide visual parameters to make monitors look similar to CRT displays without simulating their internal behavior. The tool includes features such as color corrections, B/W display colorization, antialiasing, noise effects, deconvergence, blurring/sharpening, interlacing, phosphor glow, and more. It also supports ambient lighting, vignette, integer scaling, and various image effects. Koko-aio is designed to enhance the visual experience of low-res content on high-resolution displays.

智元 Fast API is a one-stop API management system that unifies various LLM APIs in terms of format, standards, and management to achieve the ultimate in functionality, performance, and user experience. It includes features such as model management with intelligent and regex matching, backup model functionality, key management, proxy management, company management, user management, and chat management for both admin and user ends. The project supports cluster deployment, multi-site deployment, and cross-region deployment. It also provides a public API site for registration with a contact to the author for a 10 million quota. The tool offers a comprehensive dashboard, model management, application management, key management, and chat management functionalities for users.

The awesome-langchain-zh repository is a collection of resources related to LangChain, a framework for building AI applications using large language models (LLMs). The repository includes sections on the LangChain framework itself, other language ports of LangChain, tools for low-code development, services, agents, templates, platforms, open-source projects related to knowledge management and chatbots, as well as learning resources such as notebooks, videos, and articles. It also covers other LLM frameworks and provides additional resources for exploring and working with LLMs. The repository serves as a comprehensive guide for developers and AI enthusiasts interested in leveraging LangChain and LLMs for various applications.

CIA is a powerful open-source tool designed for data analysis and visualization. It provides a user-friendly interface for processing large datasets and generating insightful reports. With CIA, users can easily explore data, perform statistical analysis, and create interactive visualizations to communicate findings effectively. Whether you are a data scientist, analyst, or researcher, CIA offers a comprehensive set of features to streamline your data analysis workflow and uncover valuable insights.

Intel® Extension for Transformers is an innovative toolkit designed to accelerate GenAI/LLM everywhere with the optimal performance of Transformer-based models on various Intel platforms, including Intel Gaudi2, Intel CPU, and Intel GPU. The toolkit provides the below key features and examples: * Seamless user experience of model compressions on Transformer-based models by extending [Hugging Face transformers](https://github.com/huggingface/transformers) APIs and leveraging [Intel® Neural Compressor](https://github.com/intel/neural-compressor) * Advanced software optimizations and unique compression-aware runtime (released with NeurIPS 2022's paper [Fast Distilbert on CPUs](https://arxiv.org/abs/2211.07715) and [QuaLA-MiniLM: a Quantized Length Adaptive MiniLM](https://arxiv.org/abs/2210.17114), and NeurIPS 2021's paper [Prune Once for All: Sparse Pre-Trained Language Models](https://arxiv.org/abs/2111.05754)) * Optimized Transformer-based model packages such as [Stable Diffusion](examples/huggingface/pytorch/text-to-image/deployment/stable_diffusion), [GPT-J-6B](examples/huggingface/pytorch/text-generation/deployment), [GPT-NEOX](examples/huggingface/pytorch/language-modeling/quantization#2-validated-model-list), [BLOOM-176B](examples/huggingface/pytorch/language-modeling/inference#BLOOM-176B), [T5](examples/huggingface/pytorch/summarization/quantization#2-validated-model-list), [Flan-T5](examples/huggingface/pytorch/summarization/quantization#2-validated-model-list), and end-to-end workflows such as [SetFit-based text classification](docs/tutorials/pytorch/text-classification/SetFit_model_compression_AGNews.ipynb) and [document level sentiment analysis (DLSA)](workflows/dlsa) * [NeuralChat](intel_extension_for_transformers/neural_chat), a customizable chatbot framework to create your own chatbot within minutes by leveraging a rich set of [plugins](https://github.com/intel/intel-extension-for-transformers/blob/main/intel_extension_for_transformers/neural_chat/docs/advanced_features.md) such as [Knowledge Retrieval](./intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md), [Speech Interaction](./intel_extension_for_transformers/neural_chat/pipeline/plugins/audio/README.md), [Query Caching](./intel_extension_for_transformers/neural_chat/pipeline/plugins/caching/README.md), and [Security Guardrail](./intel_extension_for_transformers/neural_chat/pipeline/plugins/security/README.md). This framework supports Intel Gaudi2/CPU/GPU. * [Inference](https://github.com/intel/neural-speed/tree/main) of Large Language Model (LLM) in pure C/C++ with weight-only quantization kernels for Intel CPU and Intel GPU (TBD), supporting [GPT-NEOX](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptneox), [LLAMA](https://github.com/intel/neural-speed/tree/main/neural_speed/models/llama), [MPT](https://github.com/intel/neural-speed/tree/main/neural_speed/models/mpt), [FALCON](https://github.com/intel/neural-speed/tree/main/neural_speed/models/falcon), [BLOOM-7B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/bloom), [OPT](https://github.com/intel/neural-speed/tree/main/neural_speed/models/opt), [ChatGLM2-6B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/chatglm), [GPT-J-6B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptj), and [Dolly-v2-3B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptneox). Support AMX, VNNI, AVX512F and AVX2 instruction set. We've boosted the performance of Intel CPUs, with a particular focus on the 4th generation Intel Xeon Scalable processor, codenamed [Sapphire Rapids](https://www.intel.com/content/www/us/en/products/docs/processors/xeon-accelerated/4th-gen-xeon-scalable-processors.html).

LangChain is an amazing framework to get LLM projects done in a matter of no time, and the ecosystem is growing fast. Here is an attempt to keep track of the initiatives around LangChain. Subscribe to the newsletter to stay informed about the Awesome LangChain. We send a couple of emails per month about the articles, videos, projects, and tools that grabbed our attention Contributions welcome. Add links through pull requests or create an issue to start a discussion. Please read the contribution guidelines before contributing.

MNN-LLM is a high-performance inference engine for large language models (LLMs) on mobile and embedded devices. It provides optimized implementations of popular LLM models, such as ChatGPT, BLOOM, and GPT-3, enabling developers to easily integrate these models into their applications. MNN-LLM is designed to be efficient and lightweight, making it suitable for resource-constrained devices. It supports various deployment options, including mobile apps, web applications, and embedded systems. With MNN-LLM, developers can leverage the power of LLMs to enhance their applications with natural language processing capabilities, such as text generation, question answering, and dialogue generation.

L3AGI is an open-source tool that enables AI Assistants to collaborate together as effectively as human teams. It provides a robust set of functionalities that empower users to design, supervise, and execute both autonomous AI Assistants and Teams of Assistants. Key features include the ability to create and manage Teams of AI Assistants, design and oversee standalone AI Assistants, equip AI Assistants with the ability to retain and recall information, connect AI Assistants to an array of data sources for efficient information retrieval and processing, and employ curated sets of tools for specific tasks. L3AGI also offers a user-friendly interface, APIs for integration with other systems, and a vibrant community for support and collaboration.

David UI is a free and open-source collection of customizable, production-ready UI components built with Tailwind CSS. It is designed to be developer-friendly and performance-focused, streamlining the creation of modern, visually appealing interfaces to help deliver high-quality user experiences faster.

The AI Paper tool is a powerful platform for generating various types of academic papers, including graduation papers, course papers, journal papers, title papers, opening reports, task books, AIGC reduction, and custom literature. It supports unlimited revisions, AI 4.0 technology, AIGC rate reduction, custom references, outlines, feeding of materials, various types of charts and tables, multiple languages, and anonymous mode. The tool offers a wide range of paper formats and supports tasks like writing papers, assignments, internship reports, job planning, and long-form writing.

sfdx-hardis is a toolbox for Salesforce DX, developed by Cloudity, that simplifies tasks which would otherwise take minutes or hours to complete manually. It enables users to define complete CI/CD pipelines for Salesforce projects, backup metadata, and monitor any Salesforce org. The tool offers a wide range of commands that can be accessed via the command line interface or through a Visual Studio Code extension. Additionally, sfdx-hardis provides Docker images for easy integration into CI workflows. The tool is designed to be natively compliant with various platforms and tools, making it a versatile solution for Salesforce developers.

ChatGPT Infinity is a free and powerful add-on that makes ChatGPT generate infinite answers on any topic. It offers customizable topic selection, multilingual support, adjustable response interval, and auto-scroll feature for a seamless chat experience.

Intel® Neural Compressor is an open-source Python library that supports popular model compression techniques such as quantization, pruning (sparsity), distillation, and neural architecture search on mainstream frameworks such as TensorFlow, PyTorch, ONNX Runtime, and MXNet. It provides key features, typical examples, and open collaborations, including support for a wide range of Intel hardware, validation of popular LLMs, and collaboration with cloud marketplaces, software platforms, and open AI ecosystems.

The Segment Anything Model (SAM) is a powerful tool that allows users to segment any object in an image with just a few clicks. This makes it a great tool for a variety of tasks, such as object detection, tracking, and editing. SAM is also very easy to use, making it a great option for both beginners and experienced users.

InternLM-XComposer2 is a groundbreaking vision-language large model (VLLM) based on InternLM2-7B excelling in free-form text-image composition and comprehension. It boasts several amazing capabilities and applications: * **Free-form Interleaved Text-Image Composition** : InternLM-XComposer2 can effortlessly generate coherent and contextual articles with interleaved images following diverse inputs like outlines, detailed text requirements and reference images, enabling highly customizable content creation. * **Accurate Vision-language Problem-solving** : InternLM-XComposer2 accurately handles diverse and challenging vision-language Q&A tasks based on free-form instructions, excelling in recognition, perception, detailed captioning, visual reasoning, and more. * **Awesome performance** : InternLM-XComposer2 based on InternLM2-7B not only significantly outperforms existing open-source multimodal models in 13 benchmarks but also **matches or even surpasses GPT-4V and Gemini Pro in 6 benchmarks** We release InternLM-XComposer2 series in three versions: * **InternLM-XComposer2-4KHD-7B** 🤗: The high-resolution multi-task trained VLLM model with InternLM-7B as the initialization of the LLM for _High-resolution understanding_ , _VL benchmarks_ and _AI assistant_. * **InternLM-XComposer2-VL-7B** 🤗 : The multi-task trained VLLM model with InternLM-7B as the initialization of the LLM for _VL benchmarks_ and _AI assistant_. **It ranks as the most powerful vision-language model based on 7B-parameter level LLMs, leading across 13 benchmarks.** * **InternLM-XComposer2-VL-1.8B** 🤗 : A lightweight version of InternLM-XComposer2-VL based on InternLM-1.8B. * **InternLM-XComposer2-7B** 🤗: The further instruction tuned VLLM for _Interleaved Text-Image Composition_ with free-form inputs. Please refer to Technical Report and 4KHD Technical Reportfor more details.

A simple standalone viewer for reading prompt from Stable Diffusion generated image outside the webui. The tool supports macOS, Windows, and Linux, providing both GUI and CLI functionalities. Users can interact with the tool through drag and drop, copy prompt to clipboard, remove prompt from image, export prompt to text file, edit or import prompt to images, and more. It supports multiple formats including PNG, JPEG, WEBP, TXT, and various tools like A1111's webUI, Easy Diffusion, StableSwarmUI, Fooocus-MRE, NovelAI, InvokeAI, ComfyUI, Draw Things, and Naifu(4chan). Users can download the tool for different platforms and install it via Homebrew Cask or pip. The tool can be used to read, export, remove, and edit prompts from images, providing various modes and options for different tasks.

InternGPT (iGPT) is a pointing-language-driven visual interactive system that enhances communication between users and chatbots by incorporating pointing instructions. It improves chatbot accuracy in vision-centric tasks, especially in complex visual scenarios. The system includes an auxiliary control mechanism to enhance the control capability of the language model. InternGPT features a large vision-language model called Husky, fine-tuned for high-quality multi-modal dialogue. Users can interact with ChatGPT by clicking, dragging, and drawing using a pointing device, leading to efficient communication and improved chatbot performance in vision-related tasks.

Java idiomatic SDK for the Gemini Developer APIs and Vertex AI APIs. The SDK provides a Client class for interacting with both APIs, allowing seamless switching between the 2 backends without code rewriting. It supports features like generating content, embedding content, generating images, upscaling images, editing images, and generating videos. The SDK also includes options for setting API versions, HTTP request parameters, client behavior, and response schemas.

llm.rb is a zero-dependency Ruby toolkit for Large Language Models that includes OpenAI, Gemini, Anthropic, xAI (Grok), DeepSeek, Ollama, and LlamaCpp. The toolkit provides full support for chat, streaming, tool calling, audio, images, files, and structured outputs (JSON Schema). It offers a single unified interface for multiple providers, zero dependencies outside Ruby's standard library, smart API design, and optional per-provider process-wide connection pool. Features include chat, agents, media support (text-to-speech, transcription, translation, image generation, editing), embeddings, model management, and more.

StableSwarmUI is a modular Stable Diffusion web user interface that emphasizes making power tools easily accessible, high performance, and extensible. It is designed to be a one-stop-shop for all things Stable Diffusion, providing a wide range of features and capabilities to enhance the user experience.

Civitai is a platform where people can share their stable diffusion models (textual inversions, hypernetworks, aesthetic gradients, VAEs, and any other crazy stuff people do to customize their AI generations), collaborate with others to improve them, and learn from each other's work. The platform allows users to create an account, upload their models, and browse models that have been shared by others. Users can also leave comments and feedback on each other's models to facilitate collaboration and knowledge sharing.

The Segment Anything Model (SAM) is a powerful tool that allows users to segment any object in an image with just a few clicks. This makes it a great tool for a variety of tasks, such as object detection, tracking, and editing. SAM is also very easy to use, making it a great option for both beginners and experienced users.

ComfyUI-IF_AI_tools is a set of custom nodes for ComfyUI that allows you to generate prompts using a local Large Language Model (LLM) via Ollama. This tool enables you to enhance your image generation workflow by leveraging the power of language models.

Krita-AI-Diffusion is a plugin for Krita that allows users to generate images from within the program. It offers a variety of features, including inpainting, outpainting, generating images from scratch, refining existing content, live painting, and control over image creation. The plugin is designed to fit into an interactive workflow where AI generation is used as just another tool while painting. It is meant to synergize with traditional tools and the layer stack.

The AI Toolkit by Ostris is a collection of tools for machine learning, specifically designed for image generation, LoRA (latent representations of attributes) extraction and manipulation, and model training. It provides a user-friendly interface and extensive documentation to make it accessible to both developers and non-developers. The toolkit is actively under development, with new features and improvements being added regularly. Some of the key features of the AI Toolkit include: - Batch Image Generation: Allows users to generate a batch of images based on prompts or text files, using a configuration file to specify the desired settings. - LoRA (lierla), LoCON (LyCORIS) Extractor: Facilitates the extraction of LoRA and LoCON representations from pre-trained models, enabling users to modify and manipulate these representations for various purposes. - LoRA Rescale: Provides a tool to rescale LoRA weights, allowing users to adjust the influence of specific attributes in the generated images. - LoRA Slider Trainer: Enables the training of LoRA sliders, which can be used to control and adjust specific attributes in the generated images, offering a powerful tool for fine-tuning and customization. - Extensions: Supports the creation and sharing of custom extensions, allowing users to extend the functionality of the toolkit with their own tools and scripts. - VAE (Variational Auto Encoder) Trainer: Facilitates the training of VAEs for image generation, providing users with a tool to explore and improve the quality of generated images. The AI Toolkit is a valuable resource for anyone interested in exploring and utilizing machine learning for image generation and manipulation. Its user-friendly interface, extensive documentation, and active development make it an accessible and powerful tool for both beginners and experienced users.

The Clarifai Python SDK offers a comprehensive set of tools to integrate Clarifai's AI platform to leverage computer vision capabilities like classification , detection ,segementation and natural language capabilities like classification , summarisation , generation , Q&A ,etc into your applications. With just a few lines of code, you can leverage cutting-edge artificial intelligence to unlock valuable insights from visual and textual content.

The collection of pre-trained, state-of-the-art AI models. ailia SDK is a self-contained, cross-platform, high-speed inference SDK for AI. The ailia SDK provides a consistent C++ API across Windows, Mac, Linux, iOS, Android, Jetson, and Raspberry Pi platforms. It also supports Unity (C#), Python, Rust, Flutter(Dart) and JNI for efficient AI implementation. The ailia SDK makes extensive use of the GPU through Vulkan and Metal to enable accelerated computing. # Supported models 323 models as of April 8th, 2024