NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, question answering, machine translation, language detection, semantic similarity, tokenization, POS tagging, embeddings, and dependency parsing. It is ready for production, served through a REST API.
You can either use the NLP Cloud pre-trained models, fine-tune your own models, or deploy your own models.
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spaCy might be a bit more popular than NLP Cloud. We know about 59 links to it since March 2021 and only 41 links to NLP Cloud. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Is this just using LLM to be cool? How does pure LLM with simple "In the scale between 0-10"" stack up against traditional, battle-tested sentiment analysis tools? Gemini suggests NLTK and spaCy https://www.nltk.org/ https://spacy.io/. - Source: Hacker News / 9 months ago
Hi Community, In this article, I will demonstrate below steps to create your own chatbot by using spaCy (spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython):. - Source: dev.to / about 1 year ago
SpaCy: An open-source library providing tools for advanced NLP tasks like tokenization, entity recognition, and part-of-speech tagging. Source: over 1 year ago
In this article, I'm going to walk through a sentiment analysis project from start to finish, using open-source Amazon product reviews. However, using the same approach, you can easily implement mass sentiment analysis on your own products. We'll explore an approach to sentiment analysis with one of the most popular Python NLP packages: spaCy. - Source: dev.to / over 1 year ago
Spacy [0] is a state-of-art / easy-to-use NLP library from the pre-LLM era. This post is the Spacy founder's thoughts on how to integrate LLMs with the kind of problems that "traditional" NLP is used for right now. It's an advertisement for Prodigy [1], their paid tool for using LLMs to assist data labeling. That said, I think I largely agree with the premise, and it's worth reading the entire post. The steps... - Source: Hacker News / over 1 year ago
NLP Cloud (their Dolphin and Fine-tuned GPT-NeoX models). Source: almost 2 years ago
I am using NLP Cloud more and more and have not seen such quality drop with their service. Source: almost 2 years ago
You have NLP Cloud which is a nice and comprehensive OpenAI competitor. Source: almost 2 years ago
You should try NLP Cloud, they don't censor their text generation models: https://nlpcloud.com/home/playground. Source: almost 2 years ago
You can use NLP Cloud, as far as I know they don't ban anybody and don't filter NSFW. Source: almost 2 years ago
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