Best AI tools for< Generate Kernels >

Generate is an experiment to generate data from LLM. It is now deprecated.

Self-Introduction Generate AI is an innovative platform designed to assist individuals and businesses in crafting compelling and effective self-introductions. It leverages advanced AI technology to understand context and generate personalized content. The platform can analyze and understand various types of input, including text and context, to generate tailored self-introductions that are engaging and informative, enhancing personal and professional branding. With features like quick response times, quality assurance, and specialized service for self-introductions, it is an ideal tool for job applications, networking events, and personal branding initiatives.

Generate Suite is an AI-powered trend forecasting service that revolutionizes market research by offering profound insights into market trends and consumer behavior. It provides specialized assistants to jumpstart team workflows, such as scouting innovation, planning scenarios, discovering trends, and advising on brand strategy. The suite includes GenAI Agents for efficient workflows, Chat for advanced insights, Persona Generator for persona development, Ingredient Discovery Agent for food innovation, Innovation Tracker for tech advancements, Sentiment Pulse Agent for real-time insights, Subculture Scout for audience engagement, and Sustainability Scout for trend tracking and regulation insights. Generate Suite is designed to support professionals in future-ready strategies across various industries and geographies, powered by real-time data and AI technology.

ZMO.AI is a free AI image generator tool that allows users to create stunning AI art, images, anime, and realistic photos from text or images with a simple click of a button. The tool offers a full suite of powerful features to generate, remove, expand, or edit images like a pro using AI magic. With ZMO.AI, users can effortlessly generate anime and manga characters, flawless portrait photos, and realistic backgrounds. The application is trusted by over 1,000,000 users worldwide for its high-quality AI image generation capabilities.

Namelix by Brandmark.io is a free AI-powered business name generator tool that helps users create short, brandable names using artificial intelligence. The tool generates catchy names with a state-of-the-art language model, allows users to filter results based on preferences, and saves preferred names for better recommendations over time. Namelix aims to provide unique, memorable, and affordable business names for startups and new businesses, offering a solution to the limited naming options available in the market. Additionally, users can create a unique, professional logo for their business through Brandmark.io.

Dezgo is a text-to-image AI image generator powered by Stable Diffusion AI. It allows users to generate images from text descriptions. The tool offers various features such as controlled text-to-image, image-to-image upscale, inpainting from text, editing images from text, removing backgrounds, and text-to-video generation. Dezgo also provides access to models, APIs, and an affiliate program.

This free AI story generator can help you create unique and engaging stories in seconds. Simply enter a few details about your story, and our AI will generate a complete story for you. You can use this tool to generate story ideas, write short stories, or even create entire novels.

SEO Writing AI is an AI-powered writing tool that helps users create SEO-optimized articles, blog posts, and affiliate content in just a few clicks. With its user-friendly interface and advanced features, SEO Writing AI makes it easy for anyone to generate high-quality content that ranks well in search results. Some of the key features of SEO Writing AI include the ability to generate articles in over 48 languages, automatically post articles to WordPress, and optimize content for specific keywords. SEO Writing AI also offers a variety of templates and tools to help users create engaging and informative content. Overall, SEO Writing AI is a valuable tool for anyone who wants to improve their content marketing efforts.

Photo AI is an AI-powered photo generator that allows users to create realistic images of people in various poses, settings, and actions. With Photo AI, users can upload their selfies to create their own AI model, which can then be used to generate photos in any pose, place, or action. Photo AI also offers a variety of photo packs, which provide users with pre-made photo templates and prompts. Additionally, Photo AI allows users to upload clothes to dress their AI model, and to create AI-generated fashion designs with Sketch2Image.

ZMO.AI is a free AI Image Generator that allows users to create stunning AI art, images, anime, and realistic photos from text or images with a simple click of a button. The platform offers a full suite of powerful AI image generation tools, including AI Photo Editor, AI Anime Generator, AI Background Changer, AI Video Generator, and more. Trusted by over 1,000,000 users worldwide, ZMO.AI provides studio-quality photo editing capabilities, background removal, image generation, and editing features powered by AI magic. Users can easily generate high-quality anime, manga characters, portraits, and images with versatile styles using the AI tools available on the platform.

Qodo is a quality-first generative AI coding platform that helps developers write, test, and review code within IDE and Git. The platform offers automated code reviews, contextual suggestions, and comprehensive test generation, ensuring robust, reliable software development. Qodo integrates seamlessly to maintain high standards of code quality and integrity throughout the development process.

This Person Does Not Exist is a website that generates random, realistic faces of people who do not exist. The website uses a neural network called StyleGAN, developed by Nvidia, to create these faces. StyleGAN is a generative adversarial network (GAN), which is a type of machine learning algorithm that can generate new data from a given dataset. In the case of StyleGAN, the dataset is a collection of images of human faces. The GAN is trained on this dataset, and it learns to generate new faces that are realistic and indistinguishable from real faces.

NICE is a leading Customer Experience (CX) AI Platform offering a range of AI-driven solutions for businesses to enhance customer experiences, optimize workforce engagement, and improve operational efficiency. The platform provides AI companions for contact center employees, AI-driven customer self-service, AI tools for CX leaders, and actionable insights through CX analytics. NICE also offers solutions tailored for various industries such as healthcare, retail, financial services, insurance, telecom, travel, and hospitality. With a focus on transforming experiences with AI, NICE helps businesses identify behaviors that drive frictionless customer experiences, boost customer loyalty, empower agents, and drive digital transformation.

OnlyWaifus.ai is an AI-powered tool that allows users to generate uncensored, photorealistic images of anime-style female characters. The tool is easy to use and requires no technical knowledge. Users simply need to describe the waifu they want to generate, and the tool will create an image that matches their specifications. OnlyWaifus.ai offers a variety of different styles to choose from, so users can create waifus that are cute, sexy, or even dark and twisted. The tool is also constantly being updated with new features and content, so users can always find something new to enjoy.

Elai.io is an advanced tool that utilizes the power of artificial intelligence to simplify and automate the video creation process. Our aim in Elai.io is to offer a user-friendly platform that welcomes individuals at any skill level in video production. Users can outline their video’s theme and narrative through an easy-to-navigate text interface, enriching it further with various multimedia components like images, texts, and sounds. This synergy between AI and user creativity enables the crafting of videos that are rich in information and visually stunning.

Prospre is a meal planning app that helps users create personalized meal plans based on their calorie and macro goals. The app also includes a macro tracker, a recipe database, and a grocery list generator. Prospre is designed to make it easy for users to eat healthy and reach their fitness goals.

GlamGirls.ai is a website that allows users to generate AI-powered virtual girlfriends. Users can choose from a variety of different girlfriends, each with her own unique personality and appearance. GlamGirls.ai also offers a variety of features that allow users to interact with their girlfriends, such as chatting, sending gifts, and going on dates.

Blockade Labs offers Skybox AI, an immersive art generator that allows users to create 360° panoramic world experiences in 8K resolution. With Skybox AI, users can generate virtual spaces, edit details, remix styles, and transform images into 3D meshes effortlessly. The application provides a fast and efficient solution for creating visually stunning worlds using artificial intelligence technology.

Sloyd is an AI-powered 3D model generator that allows users to create 3D models from text prompts. The platform offers a wide range of features, including a huge 3D model library, easy customization of 3D models, and ready-to-use 3D models. Sloyd is ideal for game developers, designers, and 3D enthusiasts who need to create high-quality 3D models quickly and efficiently.

The AI Color Palette Generator is a web-based tool that allows users to browse, edit, visualize, and generate unique color palettes. It features a library of pre-made palettes, as well as the ability to create custom palettes from scratch. The tool also includes a variety of features to help users visualize and compare different color combinations.

KernelBench is a benchmark tool designed to evaluate Large Language Models' (LLMs) ability to generate GPU kernels. It focuses on transpiling operators from PyTorch to CUDA kernels at different levels of granularity. The tool categorizes problems into four levels, ranging from single-kernel operators to full model architectures, and assesses solutions based on compilation, correctness, and speed. The repository provides a structured directory layout, setup instructions, usage examples for running single or multiple problems, and upcoming roadmap features like additional GPU platform support and integration with other frameworks.

MInference is a tool designed to accelerate pre-filling for long-context Language Models (LLMs) by leveraging dynamic sparse attention. It achieves up to a 10x speedup for pre-filling on an A100 while maintaining accuracy. The tool supports various decoding LLMs, including LLaMA-style models and Phi models, and provides custom kernels for attention computation. MInference is useful for researchers and developers working with large-scale language models who aim to improve efficiency without compromising accuracy.

lite_llama is a llama model inference lite framework by triton. It offers accelerated inference for llama3, Qwen2.5, and Llava1.5 models with up to 4x speedup compared to transformers. The framework supports top-p sampling, stream output, GQA, and cuda graph optimizations. It also provides efficient dynamic management for kv cache, operator fusion, and custom operators like rmsnorm, rope, softmax, and element-wise multiplication using triton kernels.

KsanaLLM is a high-performance engine for LLM inference and serving. It utilizes optimized CUDA kernels for high performance, efficient memory management, and detailed optimization for dynamic batching. The tool offers flexibility with seamless integration with popular Hugging Face models, support for multiple weight formats, and high-throughput serving with various decoding algorithms. It enables multi-GPU tensor parallelism, streaming outputs, and an OpenAI-compatible API server. KsanaLLM supports NVIDIA GPUs and Huawei Ascend NPU, and seamlessly integrates with verified Hugging Face models like LLaMA, Baichuan, and Qwen. Users can create a docker container, clone the source code, compile for Nvidia or Huawei Ascend NPU, run the tool, and distribute it as a wheel package. Optional features include a model weight map JSON file for models with different weight names.

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).

ExLlamaV2 is an inference library for running local LLMs on modern consumer GPUs. It is a faster, better, and more versatile codebase than its predecessor, ExLlamaV1, with support for a new quant format called EXL2. EXL2 is based on the same optimization method as GPTQ and supports 2, 3, 4, 5, 6, and 8-bit quantization. It allows for mixing quantization levels within a model to achieve any average bitrate between 2 and 8 bits per weight. ExLlamaV2 can be installed from source, from a release with prebuilt extension, or from PyPI. It supports integration with TabbyAPI, ExUI, text-generation-webui, and lollms-webui. Key features of ExLlamaV2 include: - Faster and better kernels - Cleaner and more versatile codebase - Support for EXL2 quantization format - Integration with various web UIs and APIs - Community support on Discord

T-MAC is a kernel library that directly supports mixed-precision matrix multiplication without the need for dequantization by utilizing lookup tables. It aims to boost low-bit LLM inference on CPUs by offering support for various low-bit models. T-MAC achieves significant speedup compared to SOTA CPU low-bit framework (llama.cpp) and can even perform well on lower-end devices like Raspberry Pi 5. The tool demonstrates superior performance over existing low-bit GEMM kernels on CPU, reduces power consumption, and provides energy savings. It achieves comparable performance to CUDA GPU on certain tasks while delivering considerable power and energy savings. T-MAC's method involves using lookup tables to support mpGEMM and employs key techniques like precomputing partial sums, shift and accumulate operations, and utilizing tbl/pshuf instructions for fast table lookup.

Neural Speed is an innovative library designed to support the efficient inference of large language models (LLMs) on Intel platforms through the state-of-the-art (SOTA) low-bit quantization powered by Intel Neural Compressor. The work is inspired by llama.cpp and further optimized for Intel platforms with our innovations in NeurIPS' 2023

LoRAX is a framework that allows users to serve thousands of fine-tuned models on a single GPU, dramatically reducing the cost of serving without compromising on throughput or latency. It features dynamic adapter loading, heterogeneous continuous batching, adapter exchange scheduling, optimized inference, and is ready for production with prebuilt Docker images, Helm charts for Kubernetes, Prometheus metrics, and distributed tracing with Open Telemetry. LoRAX supports a number of Large Language Models as the base model including Llama, Mistral, and Qwen, and any of the linear layers in the model can be adapted via LoRA and loaded in LoRAX.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

The Artificial Intelligence Controller Interface (AICI) lets you build Controllers that constrain and direct output of a Large Language Model (LLM) in real time. Controllers are flexible programs capable of implementing constrained decoding, dynamic editing of prompts and generated text, and coordinating execution across multiple, parallel generations. Controllers incorporate custom logic during the token-by-token decoding and maintain state during an LLM request. This allows diverse Controller strategies, from programmatic or query-based decoding to multi-agent conversations to execute efficiently in tight integration with the LLM itself.

ChatGLM.cpp is a C++ implementation of ChatGLM-6B, ChatGLM2-6B, ChatGLM3-6B and more LLMs for real-time chatting on your MacBook. It is based on ggml, working in the same way as llama.cpp. ChatGLM.cpp features accelerated memory-efficient CPU inference with int4/int8 quantization, optimized KV cache and parallel computing. It also supports P-Tuning v2 and LoRA finetuned models, streaming generation with typewriter effect, Python binding, web demo, api servers and more possibilities.

ABQ-LLM is a novel arbitrary bit quantization scheme that achieves excellent performance under various quantization settings while enabling efficient arbitrary bit computation at the inference level. The algorithm supports precise weight-only quantization and weight-activation quantization. It provides pre-trained model weights and a set of out-of-the-box quantization operators for arbitrary bit model inference in modern architectures.

ScaleLLM is a cutting-edge inference system engineered for large language models (LLMs), meticulously designed to meet the demands of production environments. It extends its support to a wide range of popular open-source models, including Llama3, Gemma, Bloom, GPT-NeoX, and more. ScaleLLM is currently undergoing active development. We are fully committed to consistently enhancing its efficiency while also incorporating additional features. Feel free to explore our **_Roadmap_** for more details. ## Key Features * High Efficiency: Excels in high-performance LLM inference, leveraging state-of-the-art techniques and technologies like Flash Attention, Paged Attention, Continuous batching, and more. * Tensor Parallelism: Utilizes tensor parallelism for efficient model execution. * OpenAI-compatible API: An efficient golang rest api server that compatible with OpenAI. * Huggingface models: Seamless integration with most popular HF models, supporting safetensors. * Customizable: Offers flexibility for customization to meet your specific needs, and provides an easy way to add new models. * Production Ready: Engineered with production environments in mind, ScaleLLM is equipped with robust system monitoring and management features to ensure a seamless deployment experience.

Okay, here is a JSON object with the requested information about the awesome-cuda-tensorrt-fpga repository:

TornadoVM is a plug-in to OpenJDK and GraalVM that allows programmers to automatically run Java programs on heterogeneous hardware. TornadoVM targets OpenCL, PTX and SPIR-V compatible devices which include multi-core CPUs, dedicated GPUs (Intel, NVIDIA, AMD), integrated GPUs (Intel HD Graphics and ARM Mali), and FPGAs (Intel and Xilinx).

AWQ (Activation-aware Weight Quantization) is a tool designed for efficient and accurate low-bit weight quantization (INT3/4) for Large Language Models (LLMs). It supports instruction-tuned models and multi-modal LMs, providing features such as AWQ search for accurate quantization, pre-computed AWQ model zoo for various LLMs, memory-efficient 4-bit linear in PyTorch, and efficient CUDA kernel implementation for fast inference. The tool enables users to run large models on resource-constrained edge platforms, delivering more efficient responses with LLM/VLM chatbots through 4-bit inference.

**rtp-llm** is a Large Language Model (LLM) inference acceleration engine developed by Alibaba's Foundation Model Inference Team. It is widely used within Alibaba Group, supporting LLM service across multiple business units including Taobao, Tmall, Idlefish, Cainiao, Amap, Ele.me, AE, and Lazada. The rtp-llm project is a sub-project of the havenask.

OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference. It provides a common API to deliver inference solutions on various platforms, including CPU, GPU, NPU, and heterogeneous devices. OpenVINO™ supports pre-trained models from Open Model Zoo and popular frameworks like TensorFlow, PyTorch, and ONNX. Key components of OpenVINO™ include the OpenVINO™ Runtime, plugins for different hardware devices, frontends for reading models from native framework formats, and the OpenVINO Model Converter (OVC) for adjusting models for optimal execution on target devices.

AutoGPTQ is an easy-to-use LLM quantization package with user-friendly APIs, based on GPTQ algorithm (weight-only quantization). It provides a simple and efficient way to quantize large language models (LLMs) to reduce their size and computational cost while maintaining their performance. AutoGPTQ supports a wide range of LLM models, including GPT-2, GPT-J, OPT, and BLOOM. It also supports various evaluation tasks, such as language modeling, sequence classification, and text summarization. With AutoGPTQ, users can easily quantize their LLM models and deploy them on resource-constrained devices, such as mobile phones and embedded systems.

Generates Angular components based on requirements, with a focus on code-first responses.

Transforms lines into detailed prompts for visual storytelling.

Discover how your writing can shine with a unique and human style. This prompt guides you to create rich and varied texts, surprising with original twists and maintaining coherence and originality. Transform your writing and challenge AI detection tools!

Generate captions for your image and choose the vibe you like.

I generate top 10 PLG strategies in a table format

I generate viral GPT ideas based on your inputs.

Generate your eslint rule

I generate witty trash talk for fantasy football leagues.

Generate dreamy landscapes with silhouette persons

Helps you generate script keyframes, for better experience please visit museclip.ai

I generate tattoo design ideas based on your preferences.

Extract the essence of the novel story according to the quantity requirements and generate corresponding images. The images can be used directly to create novel videos.小说推文图片自动批量生成,可自动生成风格一致性图片

This GPT can generate code for you. For now it creates full-stack apps using Typescript. Just describe the feature you want and you will get a link to the Github code pull request and the live app deployed.

Generate personalized book covers

Generate Good Morning Messages for WhatsApp

I generate catchy product taglines.

I generate concise Chakra UI code from UI images or requirements.

I design Hearthstone cards and generate art.

Generate badass hacker art and profile pics.

I generate logo ideas.