Best AI tools for< Split Pdf >

pdfAssistant is a powerful AI chatbot designed to assist users with various PDF processing tasks. It offers a user-friendly chat-based interface that allows users to convert, watermark, merge, split, and perform other PDF-related operations using natural language commands. The application is powered by industry-leading PDF and AI technology, providing fast and accurate results. With pdfAssistant, users can work smarter and more efficiently by simplifying complex PDF software processes.

PDF Translator & Editor is an advanced AI-driven tool that offers multilingual document translation with format and layout preservation. It supports translating native PDF, scanned PDF, Word, Excel, PowerPoint, and image files to 136 languages. The tool also provides versatile PDF conversion and editing capabilities, such as converting PDF to images and vice versa, editing PDF text, scanning to PDF, and splitting PDF files. Powered by Google and Microsoft's Neural Machine Translation models, it ensures accurate translations and supports automatic language detection. With a global user base from over 200 countries, PDF Translator & Editor offers unlimited access without file size or page limits.

Doclingo is an AI-powered document translation tool that supports translating documents in various formats such as PDF, Word, Excel, PowerPoint, SRT subtitles, ePub ebooks, AR&ZIP packages, and more. It utilizes large language models to provide accurate and professional translations, preserving the original layout of the documents. Users can enjoy a limited-time free trial upon registration, with the option to subscribe for more features. Doclingo aims to offer high-quality translation services through continuous algorithm improvements.

HiPDF is a free online PDF solution that offers a wide range of tools for editing, converting, compressing, and organizing PDFs. It also includes AI-powered tools such as Chat with PDF and AI Detector. With HiPDF, you can easily edit PDFs in your browser, convert PDFs to and from other formats, compress PDFs to reduce their size, and merge, split, and extract images from PDFs. You can also protect your PDFs with passwords and redact sensitive information. HiPDF is a convenient and easy-to-use tool that can help you with all your PDF needs.

LightPDF is an AI-powered, free online PDF editor, converter, and reader. It offers a wide range of PDF tools, including the ability to convert PDFs to and from other formats, edit PDFs, add watermarks, split and merge PDFs, rotate PDFs, annotate PDFs, optimize PDFs, compress PDFs, perform OCR on PDFs, and protect PDFs. LightPDF also offers a variety of AI-powered features, such as an AI chatbot that can answer questions about documents and an AI-powered OCR engine that can convert scanned PDFs and images to text.

**万兴科技** is an AI-powered tool that helps users create and edit PDF documents. It offers a wide range of features, including the ability to convert PDFs to other formats, edit text and images, and add annotations. **万兴科技** is a valuable tool for anyone who needs to work with PDFs on a regular basis.

MJSplitter is a free online tool that allows users to split their Midjourney Grid images into single images. Users can either paste or upload their image grid, and the tool will automatically split the images and save them as JPEGs. The tool is not affiliated with Midjourney, and images are deleted from the server after 24 hours.

SplitSong.com is an AI tool that allows users to split songs into individual instrument tracks using Artificial Intelligence. Created by @markdoppler_, this tool enables users to upload songs or extract them from YouTube videos and separate them into specific tracks such as drums, instrumental, bass, and voice. With a user-friendly interface, SplitSong.com revolutionizes the way music enthusiasts interact with and manipulate audio tracks.

VocalRemover.org is a website that offers a simple and efficient tool to remove vocals from music tracks. Users can upload their audio files and the tool will process them to create a version with the vocals removed. The site aims to provide a hassle-free experience for users looking to create karaoke tracks or instrumental versions of songs. With a focus on performance and security, VocalRemover.org ensures a smooth process for its users.

LALAL.AI is a next-generation vocal remover and music source separation service that offers fast, easy, and precise stem extraction. It allows users to remove vocals, instrumental tracks, drums, bass, piano, electric guitar, acoustic guitar, and synthesizer tracks without compromising quality. The service leverages advanced AI technology to provide high-quality stem splitting based on cutting-edge algorithms. Users can also enjoy features like voice cleaning, voice changing, echo and reverb removal, and lead/back vocal splitting. LALAL.AI caters to both individual and business users, offering various pricing packages and enterprise solutions for seamless integration and cross-platform support.

Gaudio Studio is an AI music separation tool designed for creators to unleash their creativity with ease. It allows users to extract background music, separate instruments, and remove vocals from any music content. Powered by GSEP (Gaudio source SEParation), a high-quality and easy-to-use AI stem separation model, Gaudio Studio offers a seamless experience for audio separation. Users can upload their songs in various formats, access the tool from desktop or mobile devices, and enjoy Studio Plans for advanced processing. Additionally, Gaudio Studio can be integrated with cloud APIs and On-device SDKs for business applications, offering a versatile solution for music professionals and enthusiasts.

Music Demixer is a cutting-edge AI tool that allows users to separate songs, split stems, create instrumental breakdowns, remove vocals, extract instruments, and generate karaoke tracks. It is powered by the Demucs AI model, a winner of the Sony Music and Sound Demixing Challenges. The tool operates in the browser without cloud services, ensuring 100% privacy. Users can choose various parameters like components and quality to customize their demixing experience. Music Demixer is best experienced on a laptop or desktop and offers a free tier with limited demixes per week.

AdCopy is an AI-powered advertising platform that helps businesses create high-quality ads and optimize their ad campaigns. The platform uses AI to generate ad copy, create ad creatives, and provide insights into ad performance. AdCopy is designed to help businesses save time and money on their advertising campaigns, while also improving their results.

SplitMyExpenses is an AI-powered application designed to simplify shared expenses with friends. It allows users to create groups, split bills, track debts, and settle up seamlessly. The app offers modern design, AI receipt itemization, friend data integration from payment apps, spending visualization, and secure payment handling. With over 150 supported currencies and no limits on expenses, SplitMyExpenses revolutionizes the age-old problem of bill splitting, providing users with time, money, and sanity-saving solutions.

SplitParty is an AI-powered application that simplifies the process of splitting complicated bills with friends. Users can easily split a bill by taking a photo of the receipt, allowing the AI to identify items, quantities, and prices. The application enables users to add friends, select items ordered, and split the bill effortlessly. SplitParty Plus offers additional features such as creating groups, saving bill history, and more. Developed by @dqnamo, SplitParty is a bootstrapped indie product designed to streamline bill-splitting experiences.

SanptoBook is a personal accounting software designed to help individuals manage their finances efficiently. It offers features such as invoice and receipt management, reimbursement facilitation, tax filing assistance, bill splitting, and project tracking. The application aims to simplify financial tasks and improve overall financial organization for users. With AI-powered efficiency, SnaptoBook provides state-of-the-art receipt recognition technology and secure cloud storage for all receipts.

Splitter.ai is an AI-driven audio processing platform developed by a Swedish research company. It offers advanced audio processing technologies, including stem separation/extraction, reverb removal, and direct YouTube splitting. The platform is designed to assist music producers, DJs, artists, forensics engineers, audio engineers, karaoke enthusiasts, police, scientists, and more in enhancing their audio processing tasks. Splitter.ai aims to provide high-quality services through AI-driven solutions to meet the diverse needs of its users.

promptoMANIA is an AI art community platform with a prompt generator that allows users to create AI art using various diffusion models. Users can easily generate AI images by providing prompts and selecting different styles and references. The platform offers a user-friendly experience for beginners and experienced artists alike, enabling them to create stunning and reproducible images with the help of advanced AI technology.

StemRoller is an AI-powered application that allows users to create stems, instrumental, or acapella versions of any song. Users can simply type the name of a song into the search bar, and StemRoller will find the song online and split it into vocals, drums, bass, and other stems. Additionally, an instrumental track is created with all non-vocal stems mixed down into one track. StemRoller is free and open-source, utilizing Facebook's advanced AI and machine learning research project Demucs. Users can also donate to support the app and receive assistance on Discord for any issues or questions.

MakeBestMusic is an AI-powered music production suite that allows users to create unique music with just one click using advanced AI technology. The platform offers features such as creating instrumental and vocal music by providing simple descriptive words or lyrics, remixing music by uploading audio files and providing remix descriptions, and splitting music files to extract drums and vocals. MakeBestMusic provides a versatile approach to music creation, catering to both instrumental and vocal preferences with ease. Users can generate dynamic music, remix original audio files, and extract sounds from background music using the powerful AI music tool.

The 'ollama-ebook-summary' repository is a Python project that creates bulleted notes summaries of books and long texts, particularly in epub and pdf formats with ToC metadata. It automates the extraction of chapters, splits them into ~2000 token chunks, and allows for asking arbitrary questions to parts of the text for improved granularity of response. The tool aims to provide summaries for each page of a book rather than a one-page summary of the entire document, enhancing content curation and knowledge sharing capabilities.

The Google Cloud Document AI Samples repository contains code samples and Community Samples demonstrating how to analyze, classify, and search documents using Google Cloud Document AI. It includes various projects showcasing different functionalities such as integrating with Google Drive, processing documents using Python, content moderation with Dialogflow CX, fraud detection, language extraction, paper summarization, tax processing pipeline, and more. The repository also provides access to test document files stored in a publicly-accessible Google Cloud Storage Bucket. Additionally, there are codelabs available for optical character recognition (OCR), form parsing, specialized processors, and managing Document AI processors. Community samples, like the PDF Annotator Sample, are also included. Contributions are welcome, and users can seek help or report issues through the repository's issues page. Please note that this repository is not an officially supported Google product and is intended for demonstrative purposes only.

PaperQA is a minimal package for question and answering from PDFs or text files, providing very good answers with in-text citations. It uses OpenAI Embeddings to embed and search documents, and follows a process of embedding docs and queries, searching for top passages, creating summaries, scoring and selecting relevant summaries, putting summaries into prompt, and generating answers. Users can customize prompts and use various models for embeddings and LLMs. The tool can be used asynchronously and supports adding documents from paths, files, or URLs.

SimplerLLM is an open-source Python library that simplifies interactions with Large Language Models (LLMs) for researchers and beginners. It provides a unified interface for different LLM providers, tools for enhancing language model capabilities, and easy development of AI-powered tools and apps. The library offers features like unified LLM interface, generic text loader, RapidAPI connector, SERP integration, prompt template builder, and more. Users can easily set up environment variables, create LLM instances, use tools like SERP, generic text loader, calling RapidAPI APIs, and prompt template builder. Additionally, the library includes chunking functions to split texts into manageable chunks based on different criteria. Future updates will bring more tools, interactions with local LLMs, prompt optimization, response evaluation, GPT Trainer, document chunker, advanced document loader, integration with more providers, Simple RAG with SimplerVectors, integration with vector databases, agent builder, and LLM server.

This repository contains a sophisticated deterministic graph-based solution for answering complex questions using a controllable autonomous agent. The solution is designed to ensure that answers are solely based on the provided data, avoiding hallucinations. It involves various steps such as PDF loading, text preprocessing, summarization, database creation, encoding, and utilizing large language models. The algorithm follows a detailed workflow involving planning, retrieval, answering, replanning, content distillation, and performance evaluation. Heuristics and techniques implemented focus on content encoding, anonymizing questions, task breakdown, content distillation, chain of thought answering, verification, and model performance evaluation.

Pandrator is a GUI tool for generating audiobooks and dubbing using voice cloning and AI. It transforms text, PDF, EPUB, and SRT files into spoken audio in multiple languages. It leverages XTTS, Silero, and VoiceCraft models for text-to-speech conversion and voice cloning, with additional features like LLM-based text preprocessing and NISQA for audio quality evaluation. The tool aims to be user-friendly with a one-click installer and a graphical interface.

LongLoRA is a tool for efficient fine-tuning of long-context large language models. It includes LongAlpaca data with long QA data collected and short QA sampled, models from 7B to 70B with context length from 8k to 100k, and support for GPTNeoX models. The tool supports supervised fine-tuning, context extension, and improved LoRA fine-tuning. It provides pre-trained weights, fine-tuning instructions, evaluation methods, local and online demos, streaming inference, and data generation via Pdf2text. LongLoRA is licensed under Apache License 2.0, while data and weights are under CC-BY-NC 4.0 License for research use only.

Awesome Khmer Language is a comprehensive collection of resources for the Khmer language, including tools, datasets, research papers, projects/models, blogs/slides, and miscellaneous items. It covers a wide range of topics related to Khmer language processing, such as character normalization, word segmentation, part-of-speech tagging, optical character recognition, text-to-speech, and more. The repository aims to support the development of natural language processing applications for the Khmer language by providing a diverse set of resources and tools for researchers and developers.

OlympicArena is a comprehensive benchmark designed to evaluate advanced AI capabilities across various disciplines. It aims to push AI towards superintelligence by tackling complex challenges in science and beyond. The repository provides detailed data for different disciplines, allows users to run inference and evaluation locally, and offers a submission platform for testing models on the test set. Additionally, it includes an annotation interface and encourages users to cite their paper if they find the code or dataset helpful.

RLAIF-V is a novel framework that aligns MLLMs in a fully open-source paradigm for super GPT-4V trustworthiness. It maximally exploits open-source feedback from high-quality feedback data and online feedback learning algorithm. Notable features include achieving super GPT-4V trustworthiness in both generative and discriminative tasks, using high-quality generalizable feedback data to reduce hallucination of different MLLMs, and exhibiting better learning efficiency and higher performance through iterative alignment.

This repository, Online RLHF, focuses on aligning large language models (LLMs) through online iterative Reinforcement Learning from Human Feedback (RLHF). It aims to bridge the gap in existing open-source RLHF projects by providing a detailed recipe for online iterative RLHF. The workflow presented here has shown to outperform offline counterparts in recent LLM literature, achieving comparable or better results than LLaMA3-8B-instruct using only open-source data. The repository includes model releases for SFT, Reward model, and RLHF model, along with installation instructions for both inference and training environments. Users can follow step-by-step guidance for supervised fine-tuning, reward modeling, data generation, data annotation, and training, ultimately enabling iterative training to run automatically.

The Second Brain AI Agent Project is a tool designed to empower personal knowledge management by automatically indexing markdown files and links, providing a smart search engine powered by OpenAI, integrating seamlessly with different note-taking methods, and enhancing productivity by accessing information efficiently. The system is built on LangChain framework and ChromaDB vector store, utilizing a pipeline to process markdown files and extract text and links for indexing. It employs a Retrieval-augmented generation (RAG) process to provide context for asking questions to the large language model. The tool is beneficial for professionals, students, researchers, and creatives looking to streamline workflows, improve study sessions, delve deep into research, and organize thoughts and ideas effortlessly.

Since the emergence of chatGPT in 2022, the acceleration of Large Language Model has become increasingly important. Here is a list of papers on LLMs inference and serving.

doc2plan is a browser-based application that helps users create personalized learning plans by extracting content from documents. It features a Creator for manual or AI-assisted plan construction and a Viewer for interactive plan navigation. Users can extract chapters, key topics, generate quizzes, and track progress. The application includes AI-driven content extraction, quiz generation, progress tracking, plan import/export, assistant management, customizable settings, viewer chat with text-to-speech and speech-to-text support, and integration with various Retrieval-Augmented Generation (RAG) models. It aims to simplify the creation of comprehensive learning modules tailored to individual needs.

The 'llms' repository is a comprehensive guide on Large Language Models (LLMs), covering topics such as language modeling, applications of LLMs, statistical language modeling, neural language models, conditional language models, evaluation methods, transformer-based language models, practical LLMs like GPT and BERT, prompt engineering, fine-tuning LLMs, retrieval augmented generation, AI agents, and LLMs for computer vision. The repository provides detailed explanations, examples, and tools for working with LLMs.

This repository contains a minimal, clean code implementation of the Byte Pair Encoding (BPE) algorithm, commonly used in LLM tokenization. The BPE algorithm is "byte-level" because it runs on UTF-8 encoded strings. This algorithm was popularized for LLMs by the GPT-2 paper and the associated GPT-2 code release from OpenAI. Sennrich et al. 2015 is cited as the original reference for the use of BPE in NLP applications. Today, all modern LLMs (e.g. GPT, Llama, Mistral) use this algorithm to train their tokenizers. There are two Tokenizers in this repository, both of which can perform the 3 primary functions of a Tokenizer: 1) train the tokenizer vocabulary and merges on a given text, 2) encode from text to tokens, 3) decode from tokens to text. The files of the repo are as follows: 1. minbpe/base.py: Implements the `Tokenizer` class, which is the base class. It contains the `train`, `encode`, and `decode` stubs, save/load functionality, and there are also a few common utility functions. This class is not meant to be used directly, but rather to be inherited from. 2. minbpe/basic.py: Implements the `BasicTokenizer`, the simplest implementation of the BPE algorithm that runs directly on text. 3. minbpe/regex.py: Implements the `RegexTokenizer` that further splits the input text by a regex pattern, which is a preprocessing stage that splits up the input text by categories (think: letters, numbers, punctuation) before tokenization. This ensures that no merges will happen across category boundaries. This was introduced in the GPT-2 paper and continues to be in use as of GPT-4. This class also handles special tokens, if any. 4. minbpe/gpt4.py: Implements the `GPT4Tokenizer`. This class is a light wrapper around the `RegexTokenizer` (2, above) that exactly reproduces the tokenization of GPT-4 in the tiktoken library. The wrapping handles some details around recovering the exact merges in the tokenizer, and the handling of some unfortunate (and likely historical?) 1-byte token permutations. Finally, the script train.py trains the two major tokenizers on the input text tests/taylorswift.txt (this is the Wikipedia entry for her kek) and saves the vocab to disk for visualization. This script runs in about 25 seconds on my (M1) MacBook. All of the files above are very short and thoroughly commented, and also contain a usage example on the bottom of the file.

Python package for concise, transparent, and accurate predictive modeling. All sklearn-compatible and easy to use. _For interpretability in NLP, check out our new package:imodelsX _

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.

llm-resource is a comprehensive collection of high-quality resources for Large Language Models (LLM). It covers various aspects of LLM including algorithms, training, fine-tuning, alignment, inference, data engineering, compression, evaluation, prompt engineering, AI frameworks, AI basics, AI infrastructure, AI compilers, LLM application development, LLM operations, AI systems, and practical implementations. The repository aims to gather and share valuable resources related to LLM for the community to benefit from.

Baal is an active learning library that supports both industrial applications and research use cases. It provides a framework for Bayesian active learning methods such as Monte-Carlo Dropout, MCDropConnect, Deep ensembles, and Semi-supervised learning. Baal helps in labeling the most uncertain items in the dataset pool to improve model performance and reduce annotation effort. The library is actively maintained by a dedicated team and has been used in various research papers for production and experimentation.

Expert in PDF tasks and tool advice.

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Step 1: Upload RFP Step 2: Prompt: I need a comprehensive summary of the RFP. Split the summary in multiple blocks / section. After giving me one section wait for my command to move to the next section. Step 3: Prompt: Move to the next section, please :)

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A witty tipping calculator with literary quips.

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Provides running splits for Strava Routes, accounting for distance and elevation changes