Software Alternatives & Reviews

TextBlob VS Hugging Face

Compare TextBlob VS Hugging Face and see what are their differences

TextBlob logo TextBlob

Natural Language Processing (NLP)

Hugging Face logo Hugging Face

The Tamagotchi powered by Artificial Intelligence 🤗
  • TextBlob Landing page
    Landing page //
    2020-03-01
  • Hugging Face Landing page
    Landing page //
    2023-09-19

TextBlob videos

Natural Language Processing (Part 4): Sentiment Analysis with TextBlob in Python

More videos:

  • Tutorial - How to Calculate Sentiment Using TextBlob - Part 5 - Python Yelp Sentiment Analysis
  • Review - A Quick Guide To Sentiment Analysis | Sentiment Analysis In Python Using Textblob | Edureka

Hugging Face videos

No Hugging Face videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to TextBlob and Hugging Face)
Spreadsheets
100 100%
0% 0
Social & Communications
0 0%
100% 100
Natural Language Processing
Chatbots
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Hugging Face seems to be more popular. It has been mentiond 252 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.

TextBlob mentions (0)

We have not tracked any mentions of TextBlob yet. Tracking of TextBlob recommendations started around Mar 2021.

Hugging Face mentions (252)

  • Chat with your Github Repo using llama_index and chainlit
    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 / 16 days ago
  • AI enthusiasm - episode #1🚀
    The only requirement for this tutorial is to have an Hugging Face account. In order to get it:. - Source: dev.to / 22 days ago
  • Hosting Your Own AI Chatbot on Android Devices
    Finally, you'll need to download a compatible language model and copy it to the ~/llama.cpp/models directory. Head over to Hugging Face and search for a GGUF-formatted model that fits within your device's available RAM. I'd recommend starting with TinyLlama-1.1B. - Source: dev.to / 28 days ago
  • Sentiment Analysis with PubNub Functions and HuggingFace
    At this point, probably everyone has heard about OpenAI, GPT-4, Claude or any of the popular Large Language Models (LLMs). However, using these LLMs in a production environment can be expensive or nondeterministic regarding its results. I guess that is the downside of being good at everything; you could be better at performing one specific task. This is where HuggingFace can utilized. HuggingFace provides... - Source: dev.to / 28 days ago
  • PrivateGPT exploring the Documentation
    New models can be added by downloading GGUF format models to the models sub-directory from https://huggingface.co/. - Source: dev.to / about 1 month ago
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What are some alternatives?

When comparing TextBlob and Hugging Face, you can also consider the following products

spaCy - spaCy is a library for advanced natural language processing in Python and Cython.

Replika - Your Ai friend

Amazon Comprehend - Discover insights and relationships in text

LangChain - Framework for building applications with LLMs through composability

Google Cloud Natural Language API - Natural language API using Google machine learning

Haystack NLP Framework - Haystack is an open source NLP framework to build applications with Transformer models and LLMs.