Best AI tools for< Advance Trl >

The website 'Advance with AI' offers a range of AI tools and applications for various purposes such as content creation, image editing, and productivity enhancement. Users can access AI-powered tools like AI Writer, AI Image Generators, and AI Productivity Tools to streamline their tasks and improve efficiency. The platform also provides information on different AI categories and frequently asked questions related to AI tools and their applications.

Altair is a global leader in computational intelligence, offering software and cloud solutions in simulation, HPC, data analytics, and AI. The platform provides advanced technology for accelerating AI adoption, powering engineering processes, and enabling sustainability solutions across various industries. Altair's products and platforms cater to diverse sectors such as aerospace, automotive, healthcare, and more, with a focus on digital twin technology, generative AI, and cloud computing. The company also hosts events, webinars, and training programs to support users in leveraging their tools effectively.

Enprompt 360 is an AI-powered tool that generates chat prompts using ChatGPT technology. It provides users with a platform to create engaging and interactive conversations for various purposes such as content creation, brainstorming, and storytelling. With Enprompt 360, users can easily generate conversation starters, dialogue scenarios, and creative writing prompts. The tool leverages the power of AI to assist users in generating high-quality content efficiently and effortlessly.

MyGPT is a free, open-source user interface (UI) for ChatGPT that provides a more user-friendly and feature-rich experience. It includes features such as a code editor, a chat history, and a variety of customization options. MyGPT is designed to make it easier to use ChatGPT for a variety of tasks, including writing code, generating text, and answering questions.

Hugging Face is an AI community platform that facilitates collaboration on models, datasets, and applications within the machine learning community. It offers a wide range of tools and resources for developers and researchers to create, discover, and share machine learning projects. The platform aims to accelerate the development of AI technologies and foster innovation in the field of artificial intelligence.

DeepLearning.AI is an AI education platform offering courses and resources to help individuals start or advance their careers in artificial intelligence. Founded by renowned AI expert Andrew Ng, the platform provides a wide range of courses, specializations, newsletters, and community forums to help learners build a strong foundation in machine learning and AI skills. Subscribers can access the latest AI news, insights, and events, and benefit from the expertise of industry leaders. With a focus on practical learning and real-world applications, DeepLearning.AI aims to empower individuals to harness the power of AI and contribute to the rapidly evolving field.

Stanford HAI is a research institute at Stanford University dedicated to advancing AI research, education, and policy to improve the human condition. The institute brings together researchers from a variety of disciplines to work on a wide range of AI-related projects, including developing new AI algorithms, studying the ethical and societal implications of AI, and creating educational programs to train the next generation of AI leaders. Stanford HAI is committed to developing human-centered AI technologies and applications that benefit all of humanity.

Great Learning is an online platform offering a wide range of courses, PG certificates, and degree programs in various domains such as AI & Machine Learning, Data Science, Business Analytics, Cloud Computing, Cyber Security, Software Development, Digital Marketing, Design, MBA, and Masters. The platform provides opportunities to learn from top universities, offers career support, success stories, and enterprise solutions. With a focus on AI and Machine Learning, Great Learning aims to elevate expertise and provide transformative programs to help individuals enhance their skills and advance their careers.

Cercle is an AI platform that advances healthcare for women by transforming healthcare data into real-time, high-quality insights. The platform caters to women's healthcare providers, payors, and pharma companies, helping them run more efficient businesses and provide personalized care. Cercle's Biomedical Graph unlocks insights at unprecedented speed and accuracy, optimizing patient care and improving outcomes in areas such as assisted reproduction and fertility processes.

Pickl.AI is a platform offering professional certification courses in Data Science, empowering individuals to enhance their career prospects. The platform provides a range of courses tailored for beginners, students, and professionals, covering topics such as Machine Learning, Python programming, and Data Analytics. Pickl.AI aims to equip learners with industry-relevant skills and expertise through expert-led lectures, real projects, and doubt-clearing sessions. The platform also offers job guarantee programs and short-term courses to cater to diverse learning needs.

MealProAI is an AI-powered meal planning app that helps users create personalized meal plans based on their dietary preferences, nutritional goals, and budget. The app offers a variety of features to make meal planning easy and convenient, including the ability to select meal prep days, discover meals that match ingredients users already have, and generate meals based on available time and ingredients. MealProAI is designed to help users save time and money on meal planning and to make healthy eating more accessible.

Coursera is an online learning platform that offers courses, specializations, and degrees from top universities and companies. It provides a wide range of courses in various fields, including data science, business, computer science, health, social sciences, personal development, arts and humanities, physical science and engineering, language learning, information technology, and math and logic. Coursera also offers professional certificates and degrees that can help learners advance their careers. The platform has over 124 million users and collaborates with over 325 leading universities and companies.

Google DeepMind is a British artificial intelligence research laboratory owned by Google. The company was founded in 2010 by Demis Hassabis, Shane Legg, and Mustafa Suleyman. DeepMind's mission is to develop safe and beneficial artificial intelligence. The company's research focuses on a variety of topics, including machine learning, reinforcement learning, and computer vision. DeepMind has made significant contributions to the field of artificial intelligence, including the development of AlphaGo, the first computer program to defeat a professional human Go player.

Google DeepMind is an AI tool developed by Google with a mission to build AI responsibly to benefit humanity. The platform offers various AI technologies such as Gemini, AlphaFold, Imagen, Veo, and more, to address complex challenges across different domains. Google DeepMind focuses on research, education, and career development in the AI ecosystem, emphasizing responsibility, safety, and inclusivity. The platform aims to empower users with cutting-edge AI models and breakthroughs, enabling them to explore the transformative potential of artificial intelligence.

Saal.ai is an AI company based in Abu Dhabi that offers innovative cognitive AI solutions for various industries such as healthcare, finance, and smart cities. The company leverages artificial intelligence to develop cognitive solutions, products, and platforms that help businesses automate their operations and address challenges using advanced AI technologies. Saal.ai's framework is flexible and continuously optimized to seamlessly integrate into any business, unlocking exponential growth opportunities for humanity.

Nucleai is an AI-driven spatial biomarker analysis tool that leverages military intelligence-grade geospatial AI methods to analyze complex cellular interactions in a patient's biopsy. The platform offers a first-of-its-kind multimodal solution by ingesting images from various modalities and delivering actionable insights to optimize biomarker scoring, predict response to therapy, and revolutionize disease diagnosis and treatment.

Google DeepMind is an AI research company that aims to develop artificial intelligence technologies to benefit the world. They focus on creating next-generation AI systems to solve complex scientific and engineering challenges. Their models like Gemini, Veo, Imagen 3, SynthID, and AlphaFold are at the forefront of AI innovation. DeepMind also emphasizes responsibility, safety, education, and career opportunities in the field of AI.

Intelligent Health is the world's leading AI in medicine summit series dedicated to saving lives with AI. The platform hosts a healthtech community committed to advancing pivotal conversations on AI in medicine and fostering global collaboration across the healthcare sector. With a comprehensive agenda offering access to expert voices, Intelligent Health expedites critical discussions on challenges, solutions, and innovations to facilitate key decision-making and impactful investments. The platform aims to ensure the safe, effective, and democratic adoption of AI in healthcare to improve global health outcomes for all.

Google Research is a leading research organization focusing on advancing science and artificial intelligence. They conduct research in various domains such as AI/ML foundations, responsible human-centric technology, science & societal impact, computing paradigms, and algorithms & optimization. Google Research aims to create an environment for diverse research across different time scales and levels of risk, driving advancements in computer science through fundamental and applied research. They publish hundreds of research papers annually, collaborate with the academic community, and work on projects that impact technology used by billions of people worldwide.

The Association of Data Scientists (ADaSci) is a global professional body of AI professionals that accredits and elevates professionals with recognized certifications and transformative corporate training. They offer memberships for individuals and corporations interested in the AI field, as well as accreditations like Chartered Data Scientist (CDS) and Certified Generative AI Engineer. The organization provides continuous learning opportunities through courses and corporate training programs on topics such as generative AI and knowledge graph solutions. ADaSci aims to shape the future of AI talent by advancing expertise and achieving global recognition as certified professionals.

Chinese-Mixtral-8x7B is an open-source project based on Mistral's Mixtral-8x7B model for incremental pre-training of Chinese vocabulary, aiming to advance research on MoE models in the Chinese natural language processing community. The expanded vocabulary significantly improves the model's encoding and decoding efficiency for Chinese, and the model is pre-trained incrementally on a large-scale open-source corpus, enabling it with powerful Chinese generation and comprehension capabilities. The project includes a large model with expanded Chinese vocabulary and incremental pre-training code.

This repository contains convenience scripts to finetune LLaMa3-8B (or any other foundation model) for chat towards any language (that isn't English). The rationale behind this is that LLaMa3 is trained on primarily English data and while it works to some extent for other languages, its performance is poor compared to English.

LLaMa2lang is a repository containing convenience scripts to finetune LLaMa3-8B (or any other foundation model) for chat towards any language that isn't English. The repository aims to improve the performance of LLaMa3 for non-English languages by combining fine-tuning with RAG. Users can translate datasets, extract threads, turn threads into prompts, and finetune models using QLoRA and PEFT. Additionally, the repository supports translation models like OPUS, M2M, MADLAD, and base datasets like OASST1 and OASST2. The process involves loading datasets, translating them, combining checkpoints, and running inference using the newly trained model. The repository also provides benchmarking scripts to choose the right translation model for a target language.

ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher

This repository does not provide a tool, but rather a collection of resources and strategies for academics in the field of artificial intelligence who are feeling depressed or overwhelmed by the rapid advancements in the field. The resources include articles, blog posts, and other materials that offer advice on how to cope with the challenges of working in a fast-paced and competitive environment.

The Keras-llm-robot Web UI project is an open-source tool designed for offline deployment and testing of various open-source models from the Hugging Face website. It allows users to combine multiple models through configuration to achieve functionalities like multimodal, RAG, Agent, and more. The project consists of three main interfaces: chat interface for language models, configuration interface for loading models, and tools & agent interface for auxiliary models. Users can interact with the language model through text, voice, and image inputs, and the tool supports features like model loading, quantization, fine-tuning, role-playing, code interpretation, speech recognition, image recognition, network search engine, and function calling.

ALMA (Advanced Language Model-based Translator) is a many-to-many LLM-based translation model that utilizes a two-step fine-tuning process on monolingual and parallel data to achieve strong translation performance. ALMA-R builds upon ALMA models with LoRA fine-tuning and Contrastive Preference Optimization (CPO) for even better performance, surpassing GPT-4 and WMT winners. The repository provides ALMA and ALMA-R models, datasets, environment setup, evaluation scripts, training guides, and data information for users to leverage these models for translation tasks.

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).

Unsloth is a tool that allows users to fine-tune large language models (LLMs) 2-5x faster with 80% less memory. It is a free and open-source tool that can be used to fine-tune LLMs such as Gemma, Mistral, Llama 2-5, TinyLlama, and CodeLlama 34b. Unsloth supports 4-bit and 16-bit QLoRA / LoRA fine-tuning via bitsandbytes. It also supports DPO (Direct Preference Optimization), PPO, and Reward Modelling. Unsloth is compatible with Hugging Face's TRL, Trainer, Seq2SeqTrainer, and Pytorch code. It is also compatible with NVIDIA GPUs since 2018+ (minimum CUDA Capability 7.0).

This repository contains a curated list of resources on generative information retrieval, including research papers, datasets, tools, and applications. Generative information retrieval is a subfield of information retrieval that uses generative models to generate new documents or passages of text that are relevant to a given query. This can be useful for a variety of tasks, such as question answering, summarization, and document generation. The resources in this repository are intended to help researchers and practitioners stay up-to-date on the latest advances in generative information retrieval.

LLaMA Factory is a unified framework for fine-tuning 100+ large language models (LLMs) with various methods, including pre-training, supervised fine-tuning, reward modeling, PPO, DPO and ORPO. It features integrated algorithms like GaLore, BAdam, DoRA, LongLoRA, LLaMA Pro, LoRA+, LoftQ and Agent tuning, as well as practical tricks like FlashAttention-2, Unsloth, RoPE scaling, NEFTune and rsLoRA. LLaMA Factory provides experiment monitors like LlamaBoard, TensorBoard, Wandb, MLflow, etc., and supports faster inference with OpenAI-style API, Gradio UI and CLI with vLLM worker. Compared to ChatGLM's P-Tuning, LLaMA Factory's LoRA tuning offers up to 3.7 times faster training speed with a better Rouge score on the advertising text generation task. By leveraging 4-bit quantization technique, LLaMA Factory's QLoRA further improves the efficiency regarding the GPU memory.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

IPEX-LLM is a PyTorch library for running Large Language Models (LLMs) on Intel CPUs and GPUs with very low latency. It provides seamless integration with various LLM frameworks and tools, including llama.cpp, ollama, Text-Generation-WebUI, HuggingFace transformers, and more. IPEX-LLM has been optimized and verified on over 50 LLM models, including LLaMA, Mistral, Mixtral, Gemma, LLaVA, Whisper, ChatGLM, Baichuan, Qwen, and RWKV. It supports a range of low-bit inference formats, including INT4, FP8, FP4, INT8, INT2, FP16, and BF16, as well as finetuning capabilities for LoRA, QLoRA, DPO, QA-LoRA, and ReLoRA. IPEX-LLM is actively maintained and updated with new features and optimizations, making it a valuable tool for researchers, developers, and anyone interested in exploring and utilizing LLMs.

A comprehensive repository of resources for Chinese large language models (LLMs), including data processing tools, fine-tuning frameworks, inference libraries, evaluation platforms, RAG engines, agent frameworks, books, courses, tutorials, and tips. The repository covers a wide range of tools and resources for working with LLMs, from data labeling and processing to model fine-tuning, inference, evaluation, and application development. It also includes resources for learning about LLMs through books, courses, and tutorials, as well as insights and strategies from building with LLMs.

Liger Kernel is a collection of Triton kernels designed for LLM training, increasing training throughput by 20% and reducing memory usage by 60%. It includes Hugging Face Compatible modules like RMSNorm, RoPE, SwiGLU, CrossEntropy, and FusedLinearCrossEntropy. The tool works with Flash Attention, PyTorch FSDP, and Microsoft DeepSpeed, aiming to enhance model efficiency and performance for researchers, ML practitioners, and curious novices.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.

Assess the TRL of your projects, get ideas for specific TRLs, learn how to advance from one TRL to the next

A guide on healthcare legal planning

Advanced financial advisor for business and personal finance, with a focus on New Zealand.

Advance your Python skills and break through tough coding problems with expert mentoring, blending real-world wisdom and cutting-edge techniques.

I guide you towards cosmic-scale ideas that help advance humanity.

An AI tool offering expert advice on financial products, focusing on Top Loan Apps, best lending apps, fast cash advance apps, online loan apps, instant loan apps, and emergency loan apps. This tool provides insights, comparisons, and guidance for users seeking quick and reliable loan solutions.

Expert AI Architect for Advancing Complexities in AI Understanding

Una guía completa para autodidactas

A guide for Canadian police recruitment and education.

Expert in MBA application consulting with a focus on top-tier programs

Male Compass

Mentorship concierge, focused on matching you with human mentors.

I find classical music career opportunities in table format.

Harmonizing Challenge and Skill: Learn with the perfect amount of challenge.

An educational guide for respiratory therapists, covering a wide range of relevant topics.

A career coach aiding in writing self-evaluations.

A professional education teacher offering guidance in vocational fields.

Your personal CISSP Instructor

Brian's career insights

I specialize in job searches in 34 countries and offer general career advice.