word2vecGoogle
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Related Products
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About
The aim of GLTR is to take the same models that are used to generated fake text as a tool for detection. GLTR has access to the GPT-2 117M language model from OpenAI, one of the largest publicly available models. It can use any textual input and analyze what GPT-2 would have predicted at each position. Since the output is a ranking of all of the words that the model knows, we can compute how the observed following word ranks. We use this positional information to overlay a colored mask over the text that corresponds to the position in the ranking. A word that ranks within the most likely words is highlighted in green (top 10), yellow (top 100), red (top 1,000), and the rest of the words in purple. Thus, we can get a direct visual indication of how likely each word was under the model.
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About
Word2Vec is a neural network-based technique for learning word embeddings, developed by researchers at Google. It transforms words into continuous vector representations in a multi-dimensional space, capturing semantic relationships based on context. Word2Vec uses two main architectures: Skip-gram, which predicts surrounding words given a target word, and Continuous Bag-of-Words (CBOW), which predicts a target word based on surrounding words. By training on large text corpora, Word2Vec generates word embeddings where similar words are positioned closely, enabling tasks like semantic similarity, analogy solving, and text clustering. The model was influential in advancing NLP by introducing efficient training techniques such as hierarchical softmax and negative sampling. Though newer embedding models like BERT and Transformer-based methods have surpassed it in complexity and performance, Word2Vec remains a foundational method in natural language processing and machine learning research.
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Not Supported
On-Premises
Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Users that need a tool to detect AI generated content
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Audience
Researchers, data scientists, and developers working in natural language processing (NLP) and machine learning who need efficient word embeddings for text analysis and semantic understanding
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
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Support
Phone Support
Not Supported
24/7 Live Support
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Online
Not Supported
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API
Offers API
Not Supported
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API
Offers API
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Screenshots and Videos |
Screenshots and VideosNo images available
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Pricing
Free
Free Version
Supported
Free Trial
Not Supported
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Pricing
Free
Open source
Free Version
Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Not Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationGLTR
United States
gltr.io
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Company InformationGoogle
Founded: 1998
United States
code.google.com/archive/p/word2vec/
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Categories |
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Integrations
ChatGPT
Supported
GPT-3
Supported
GPT-4
Supported
Gensim
Not Supported
OpenAI
Supported
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Integrations
ChatGPT
Not Supported
GPT-3
Not Supported
GPT-4
Not Supported
Gensim
Supported
OpenAI
Not Supported
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