Fluent Read is an open-source browser translation plugin designed to provide a seamless web page translation experience. It offers efficient translation methods, dual language modes, and customizable settings to help users overcome language barriers and enjoy a native-like reading experience across the web.
Read smoothly.
An AI translation engine that understands context will provide a more user-friendly translation for websites, allowing everyone to have a reading experience in their native language.
Introduction
Feature
🌐 Dual Language and Translation Modes
- Dual language mode: Display both original and translated text
- Translation mode: Show only the translated text
- Enhances reading experience by offering flexibility in content display
🖱️ Multiple Translation Methods
- Quick translation: Hover and use shortcut keys (Ctrl, Alt, Shift, or Backtick)
- Mouse translation: Double-click, long-press, or single-click mouse wheel
- Drag-and-drop translation: Hold shortcut key and select text
- Touch translation: Support for various multi-finger gestures
🆓 Free and Open-Source
- Licensed under GPL-3.0
- Source code available on GitHub
- No subscription or payment required
⚙️ Customizable Settings
- Adjust translation settings to personal preferences
- Customize shortcut keys for optimal user experience
🌍 Browser Compatibility
- Primarily designed for Chrome
- Manual installation possible for other browsers
FAQ
Is Fluent Read a paid plugin?
No, Fluent Read is completely free to use.
Can I customize the translation settings?
Yes, you can customize both the translation settings and shortcut keys to suit your needs.
Is Fluent Read compatible with all browsers?
Fluent Read is primarily designed for Chrome, but it can be used with other browsers through manual installation of the plugin.
How can I get the most out of Fluent Read?
Try experimenting with the dual language mode and different translation methods to find the setup that works best for you. If you encounter any issues or have suggestions, visit the developer's support site for assistance.
Latest Traffic Insights
Monthly Visits
193.90 M
Bounce Rate
56.27%
Pages Per Visit
2.71
Time on Site(s)
115.91
Global Rank
-
Country Rank
-
Recent Visits
Traffic Sources
- Social Media:0.48%
- Paid Referrals:0.55%
- Email:0.15%
- Referrals:12.81%
- Search Engines:16.21%
- Direct:69.81%
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)
* 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.](https://static.right-ai.com/tools/2024/7/3/chromewebstore-google-com-detail-chatgpt-for-google-for-fr-pabeminldebomngnkgffiejipjjaaogi-thumbnail-1720037311.png "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.")
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.
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.How to Add ChatGPT to All Google Searches ===================================================== Step 1: Create a Custom Search Engine -------------------------------------- * Go to the [Google Custom Search Engine](https://cse.google.com/) website and sign in with your Google account. * Click on the "New Search Engine" button. * Fill in the required information, such as the name and description of your search engine. * Click on the "Create" button. Step 2: Add ChatGPT to the Search Engine ----------------------------------------- * In the "Setup" tab, click on the "Add" button next to "Sites to search". * Enter the following URL: `https://chat.openai.com/` * Click on the "Add" button. Step 3: Configure the Search Engine -------------------------------------- * In the "Setup" tab, click on the "Edit" button next to "Search engine keywords". * Add the following keywords: `ChatGPT` * Click on the "Save" button. Step 4: Get the Search Engine Code ------------------------------------- * In the "Setup" tab, click on the "Get code" button. * Copy the HTML code provided. Step 5: Add the Search Engine to Your Browser ------------------------------------------------ * Open your browser and go to the "Settings" or "Options" page. * Look for the "Search engine" or "Default search engine" option. * Click on the "Add" or "Manage search engines" button. * Paste the HTML code you copied earlier. * Click on the "Add" or "Save" button. You're Done! =============== Now, whenever you search on Google, ChatGPT will be included in the search results. You can also use the custom search engine URL provided by Google to search directly.
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