word2vec

word2vec

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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.

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.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Users that need a tool to detect AI generated content

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

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

No images available

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

GLTR
United States
gltr.io

Company Information

Google
Founded: 1998
United States
code.google.com/archive/p/word2vec/

Alternatives

GPTKit

GPTKit

Dreamsoft Innovations

Alternatives

Gensim

Gensim

Radim Řehůřek
AI Detector Pro (AIDP)

AI Detector Pro (AIDP)

AI Detector Pro
GloVe

GloVe

Stanford NLP

Categories

Categories

Integrations

ChatGPT
GPT-3
GPT-4
Gensim
OpenAI

Integrations

ChatGPT
GPT-3
GPT-4
Gensim
OpenAI
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