Best Natural Language Processing Software for Python

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ChatGPT is an AI-powered conversational assistant developed by OpenAI that helps users with writing, learning, brainstorming, coding, and more. It is free to use with easy access via web and apps on multiple devices. Users can interact through typing or voice to get answers, generate creative content, summarize information, and automate tasks. The platform supports various use cases, from casual questions to complex research and coding help. ChatGPT offers multiple subscription plans, including Free, Plus, and Pro, with increasing access to advanced AI models and features. It is designed to boost productivity and creativity for individuals, students, professionals, and developers alike.

Mistral AI is a pioneering artificial intelligence startup specializing in open-source generative AI. The company offers a range of customizable, enterprise-grade AI solutions deployable across various platforms, including on-premises, cloud, edge, and devices. Flagship products include "Le Chat," a multilingual AI assistant designed to enhance productivity in both personal and professional contexts, and "La Plateforme," a developer platform that enables the creation and deployment of AI-powered applications. Committed to transparency and innovation, Mistral AI positions itself as a leading independent AI lab, contributing significantly to open-source AI and policy development.

Cohere is an enterprise AI platform that enables developers and businesses to build powerful language-based applications. Specializing in large language models (LLMs), Cohere provides solutions for text generation, summarization, and semantic search. Their model offerings include the Command family for high-performance language tasks and Aya Expanse for multilingual applications across 23 languages. Focused on security and customization, Cohere allows flexible deployment across major cloud providers, private cloud environments, or on-premises setups to meet diverse enterprise needs. The company collaborates with industry leaders like Oracle and Salesforce to integrate generative AI into business applications, improving automation and customer engagement. Additionally, Cohere For AI, their research lab, advances machine learning through open-source projects and a global research community.

Claude is an artificial intelligence large language model that can process and generate human-like text. Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. Large, general systems of today can have significant benefits, but can also be unpredictable, unreliable, and opaque: our goal is to make progress on these issues. For now, we’re primarily focused on research towards these goals; down the road, we foresee many opportunities for our work to create value commercially and for public benefit.

GPT-4o (“o” for “omni”) is a step towards much more natural human-computer interaction—it accepts as input any combination of text, audio, image, and video and generates any combination of text, audio, and image outputs. It can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time (opens in a new window) in a conversation. It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50% cheaper in the API. GPT-4o is especially better at vision and audio understanding compared to existing models.

We’ve trained a model called ChatGPT which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer followup questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests. ChatGPT is a sibling model to InstructGPT, which is trained to follow an instruction in a prompt and provide a detailed response. ChatGPT Plus is a subscription plan for ChatGPT a conversational AI. ChatGPT Plus costs $20/month, and subscribers will receive a number of benefits: - General access to ChatGPT, even during peak times - Faster response times - GPT-4 access - ChatGPT plugins - Web-browsing with ChatGPT - Priority access to new features and improvements ChatGPT Plus is available to customers in the United States, and we will begin the process of inviting people from our waitlist over the coming weeks. We plan to expand access and support to additional countries and regions soon.

As AI becomes more advanced, it will solve increasingly complex and critical problems. It also takes significantly more compute to power these capabilities. ChatGPT Pro is a $200 monthly plan that enables scaled access to the best of OpenAI’s models and tools. This plan includes unlimited access to our smartest model, OpenAI o1, as well as to o1-mini, GPT-4o, and Advanced Voice. It also includes o1 pro mode, a version of o1 that uses more compute to think harder and provide even better answers to the hardest problems. In the future, we expect to add more powerful, compute-intensive productivity features to this plan. ChatGPT Pro provides access to a version of our most intelligent model that thinks longer for the most reliable responses. In evaluations from external expert testers, o1 pro mode produces more reliably accurate and comprehensive responses, especially in areas like data science, programming, and case law analysis.

Fast and accurate AI models suited for production. Highly-available inference API leveraging the most advanced NVIDIA GPUs. We selected the best open-source natural language processing (NLP) models from the community and deployed them for you. Fine-tune your own models - including GPT-J - or upload your in-house custom models, and deploy them easily to production. Upload or Train/Fine-Tune your own AI models - including GPT-J - from your dashboard, and use them straight away in production without worrying about deployment considerations like RAM usage, high-availability, scalability... You can upload and deploy as many models as you want to production.

AI21 Studio provides API access to Jurassic-1 large-language-models. Our models power text generation and comprehension features in thousands of live applications. Take on any language task. Our Jurassic-1 models are trained to follow natural language instructions and require just a few examples to adapt to new tasks. Use our specialized APIs for common tasks like summarization, paraphrasing and more. Access superior results at a lower cost without reinventing the wheel. Need to fine-tune your own custom model? You're just 3 clicks away. Training is fast, affordable and trained models are deployed immediately. Give your users superpowers by embedding an AI co-writer in your app. Drive user engagement and success with features like long-form draft generation, paraphrasing, repurposing and custom auto-complete.

Experience the power of large language models like never before, unleashing the full potential of Natural Language Processing (NLP) with Spark NLP, the open source library that delivers scalable LLMs. The full code base is open under the Apache 2.0 license, including pre-trained models and pipelines. The only NLP library built natively on Apache Spark. The most widely used NLP library in the enterprise. Spark ML provides a set of machine learning applications that can be built using two main components, estimators and transformers. The estimators have a method that secures and trains a piece of data to such an application. The transformer is generally the result of a fitting process and applies changes to the target dataset. These components have been embedded to be applicable to Spark NLP. Pipelines are a mechanism for combining multiple estimators and transformers in a single workflow. They allow multiple chained transformations along a machine-learning task.

Gensim is a free, open source Python library designed for unsupervised topic modeling and natural language processing, focusing on large-scale semantic modeling. It enables the training of models like Word2Vec, FastText, Latent Semantic Analysis (LSA), and Latent Dirichlet Allocation (LDA), facilitating the representation of documents as semantic vectors and the discovery of semantically related documents. Gensim is optimized for performance with highly efficient implementations in Python and Cython, allowing it to process arbitrarily large corpora using data streaming and incremental algorithms without loading the entire dataset into RAM. It is platform-independent, running on Linux, Windows, and macOS, and is licensed under the GNU LGPL, promoting both personal and commercial use. The library is widely adopted, with thousands of companies utilizing it daily, over 2,600 academic citations, and more than 1 million downloads per week.

The Natural Language Toolkit (NLTK) is a comprehensive, open source Python library designed for human language data processing. It offers user-friendly interfaces to over 50 corpora and lexical resources, such as WordNet, along with a suite of text processing libraries for tasks including classification, tokenization, stemming, tagging, parsing, and semantic reasoning. NLTK also provides wrappers for industrial-strength NLP libraries and maintains an active discussion forum. Accompanied by a hands-on guide that introduces programming fundamentals alongside computational linguistics topics, and comprehensive API documentation, NLTK is suitable for linguists, engineers, students, educators, researchers, and industry professionals. It is compatible with Windows, Mac OS X, and Linux platforms. Notably, NLTK is a free, community-driven project.

Integrate our text analytics APIs to add world-leading NLP into your product, platform, or application. The most feature-complete NLP feature stack on the market, 19 years in development and constantly being improved with new libraries, configurations, and models. Determine whether a piece of writing is positive, negative, or neutral. Sort and organize documents into customizable groups. Determine the expressed intent of customers and reviewers. Find people, places, dates, companies, products, jobs, titles, and more. Deploy our text analytics and NLP systems across any combination of on-premise, private cloud, hybrid cloud, and public cloud infrastructure. Our core text analytics and natural language processing software libraries are at your command. Suitable for data scientists and architects who want complete access to the underlying technology or who need on-premise deployment for security or privacy reasons.

Text analytics and NLP software libraries for on-premise deployment or integration. Integrate Salience into your enterprise business intelligence architecture or white label it inside your own data analytics product. Salience can process 200 tweets per second while scaling from single process cores to entire data centers with a small memory footprint. Use Java, Python, .NET/C# bindings for higher level ease or the native C/C++ interface for maximum speed. Enjoy full access to the underlying technology. Tune every text analytics function and NLP feature, from tokenization and part of speech tagging to sentiment scoring, categorization, theme analysis, and more. Built on a pipeline model of NLP rules and machine learning models. When issues arise, see exactly where they are in the pipeline. Adjust specific features without disrupting the larger system. Salience runs entirely on your servers while staying flexible enough to offload insensitive data to cloud servers.

The MindMeld Conversational AI Platform is a Python-based machine learning framework that encompasses all of the algorithms and utilities required for building production-quality conversational applications. Evolved over several years of building and deploying dozens of advanced interfaces, MindMeld is optimized for building conversational assistants which demonstrate deep understanding of a particular use case or domain while providing highly useful and versatile conversational experiences. Powerful command-line utilities and Python APIs with the flexibility to accommodate nearly any product requirements. Access to state-of-the-art machine learning algorithms and streamlined management of large sets of custom training data. Enhanced entity recognition and resolution to deal with automatic speech recognition (ASR) errors.

TextBlob is a Python library for processing textual data, offering a simple API to perform common natural language processing tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, and classification. It stands on the giant shoulders of NLTK and Pattern, and plays nicely with both. Key features include tokenization (splitting text into words and sentences), word and phrase frequencies, parsing, n-grams, word inflection (pluralization and singularization) lemmatization, spelling correction, and WordNet integration. TextBlob is compatible with Python versions 2.7 and above, and 3.5 and above. It is actively developed on GitHub and is licensed under the MIT License. Comprehensive documentation, including a quick start guide and tutorials, is available to assist users in implementing various NLP tasks.