NEURONwriter is an AI-powered tool for writing and optimizing content for SEO. With a user-friendly interface and advanced content editor, it is designed to help you quickly write and optimize high-quality SEO-friendly content.
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Moment One
Whole
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GoodMind
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FeelsFM
Hugging Face
Replika
LangChain
Mitsuku
Haystack NLP Framework
Cleverbot.io
Kuki
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Moment One Hugging FaceBased on our record, Hugging Face seems to be more popular. It has been mentiond 256 times since March 2021. 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.
These libraries are fundamental for building and training our GPT model. PyTorch is a deep learning framework that provides flexibility and speed, while the Transformers library by Hugging Face offers pre-trained models and tokenizers, including GPT-2. - Source: dev.to / about 14 hours ago
Hugging Face is a company and community platform making AI accessible through open-source tools, libraries, and models. It is most notable for its transformers Python library, built for natural language processing applications. This library provides developers a way to integrate ML models hosted on Hugging Face into their projects and build comprehensive ML pipelines. - Source: dev.to / 9 days ago
We will use the OpenAI embeddings API to convert the content of the blog posts into vector embeddings. You will need to sign up for an API key on the OpenAI website to use the API. You will need to provide your credit card information as there is a cost associated with using the API. You can review the pricing on the OpenAI website. There are alternatives to generate embeddings. Hugging Face provides... - Source: dev.to / 8 days ago
Hugging-face 🤗 is a repository to host all the LLM models available in the world. https://huggingface.co/. - Source: dev.to / 15 days ago
HuggingFaceEmbeddings is a function that we use for converting our documents to vector which is called embedding, you can use any embedding model from huggingface, it will load the model on your local computer and create embeddings(you can use external api/service to create embeddings), then we just pass this to context and create index and store them into folder so we can reuse them and don't need to recalculate it. - Source: dev.to / about 2 months ago
Whole - Self care habit builder to improve your mental health
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LangChain - Framework for building applications with LLMs through composability
GoodMind - AI-powered assessments & stigma-free counselling sessions
Mitsuku - Browser-based, AI chat bot.