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TaggingBox

A new way to manage your knowledge! Just like sticking a sticker on an important note, we recommend the best tags for your information.
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TaggingBox
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Introduction

Tagging Box is a browser extension designed to revolutionize knowledge and information management. It enables users to easily tag and organize their web browsing experience through innovative features like sentence dragging and AI-powered tag recommendations. Supporting multiple languages and prioritizing user privacy, Tagging Box offers a seamless way to categorize and manage online information.

Feature

Sentence Dragging

Tagging Box allows users to drag and drop sentences to recommend relevant tags, simplifying the process of categorizing information.

AI-Powered Tag Recommendation

The extension utilizes a GPT 4.0-based API service to analyze sentence context and suggest the most appropriate tags.

Multi-Language Support

Tagging Box supports multiple languages, including Korean and English, making it versatile for use with web pages from various regions.

Personal Data Protection

User privacy is a top priority. Tagging Box does not collect or store any personal information or browsing history.

Easy Installation and Use

  1. Install the Tagging Box browser extension from the Chrome Web Store
  2. Drag and drop sentences to recommend tags
  3. Utilize the AI-powered tag recommendation system
  4. Organize tagged information into a personalized knowledge base

Flexible Pricing

Tagging Box offers a free version with optional premium features available for paid subscribers.

FAQ

How does Tagging Box work?

Tagging Box combines sentence dragging and AI-powered tag recommendation systems to help users categorize information efficiently.

Is Tagging Box free to use?

Yes, Tagging Box is free to use, with optional premium features available for paid subscribers.

Does Tagging Box collect or store personal information?

No, Tagging Box prioritizes user privacy and does not collect or store any personal information or browsing history.

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Think of it like a blockchain for AI:

* Transparency:  The decision-making processes of decentralized AI are open and visible to everyone.
* Security:  Since there's no single point of failure, it's harder for malicious actors to take control or manipulate the system.
* Resilience:  Even if some nodes go offline, the network can continue to function.
* Accessibility:  Decentralized AI can make AI technology more accessible to individuals and smaller organizations.


There are many potential applications for decentralized AI, including:

* Data privacy:  Decentralized AI can help protect user data by distributing it across multiple nodes.
* Fairness and bias mitigation:  By involving a wider range of participants in the training process, decentralized AI can help reduce bias in AI systems.
* Autonomous organizations:  Decentralized AI can be used to create self-governing organizations that operate without human intervention.



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You can now access ChatGPT, a powerful language model, for free with Google. Here's how:

Method 1: Google Colab

* Open Google Colab ([colab.research.google.com](http://colab.research.google.com))
* Create a new notebook
* Install the `transformers` library by running `!pip install transformers`
* Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')`
* Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))`

Method 2: Google Apps Script

* Open Google Apps Script ([script.google.com](http://script.google.com))
* Create a new project
* Install the `transformers` library by running `npm install transformers`
* Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');`
* Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));`

Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.
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Get ChatGPT for Free with Google You can now access ChatGPT, a powerful language model, for free with Google. Here's how: Method 1: Google Colab * Open Google Colab ([colab.research.google.com](http://colab.research.google.com)) * Create a new notebook * Install the `transformers` library by running `!pip install transformers` * Import the `transformers` library and load the ChatGPT model using `from transformers import AutoModelForCausalLM, AutoTokenizer; model = AutoModelForCausalLM.from_pretrained('chatgpt'); tokenizer = AutoTokenizer.from_pretrained('chatgpt')` * Use the model to generate text using `input_text = "Your input here"; inputs = tokenizer.encode_plus(input_text, return_tensors='pt', max_length=1024, padding='max_length', truncation=True); output = model(inputs['input_ids'], attention_mask=inputs['attention_mask']); print(tokenizer.decode(output.logits[0], skip_special_tokens=True))` Method 2: Google Apps Script * Open Google Apps Script ([script.google.com](http://script.google.com)) * Create a new project * Install the `transformers` library by running `npm install transformers` * Import the `transformers` library and load the ChatGPT model using `const { AutoModelForCausalLM, AutoTokenizer } = require('transformers'); const model = new AutoModelForCausalLM('chatgpt'); const tokenizer = new AutoTokenizer('chatgpt');` * Use the model to generate text using `const inputText = "Your input here"; const inputs = tokenizer.encodePlus(inputText, { return_tensors: 'pt', max_length: 1024, padding: 'max_length', truncation: true }); const output = model(inputs.inputIds, inputs.attentionMask); console.log(tokenizer.decode(output.logits[0], { skipSpecialTokens: true }));` Note: These methods require some technical knowledge and may have limitations compared to the original ChatGPT model.

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