Kaspian is an innovative search engine designed to provide precise and contextual results. It goes beyond traditional search capabilities by understanding context, language, behavior, and relationships. Kaspian offers personalized search results by connecting data from various apps and indexing it efficiently. This powerful tool is accessible through a Chrome extension, making it easy for users to find exactly what they need and discover important information across their applications.
Kaspian
Kaspian searches through all your apps to help you find exactly what you need and discover things you should know.
Introduction
Feature
Contextual Search
Kaspian's advanced search engine comprehends context, language, behavior, and relationships, delivering instant answers to all user queries.
Personalized Results
By connecting data from all your apps and indexing it in a state-of-the-art search engine, Kaspian provides highly relevant and personalized search results.
Free Search Functionality
Users can enjoy unrestricted search capabilities across all their apps without any limitations, making Kaspian accessible to everyone.
Chrome Extension
Kaspian is easily accessible through a Chrome extension, simplifying the installation process and integration into users' browsing experience.
Data Privacy and Security
Kaspian prioritizes user privacy by not using personal data for training purposes and keeping all information confidential and secure.
FAQ
How do I start using Kaspian?
To begin using Kaspian:
- Install the Kaspian extension from the Chrome Web Store
- Once installed, use the Kaspian search bar to enter your queries
- Explore the features and functionalities to maximize your experience
Is Kaspian completely free to use?
Yes, Kaspian offers free search functionality allowing users to search across all their apps without limitations. However, a subscription may be required for more advanced features.
How does Kaspian ensure data privacy?
Kaspian maintains data privacy by:
- Not using user data for training purposes
- Keeping all user information confidential and secure
What makes Kaspian's search results unique?
Kaspian's search results are unique due to:
- Contextual understanding of queries
- Personalization based on user data from various apps
- Efficient indexing using a state-of-the-art search engine
Latest Traffic Insights
Monthly Visits
205.80 M
Bounce Rate
55.76%
Pages Per Visit
2.73
Time on Site(s)
117.23
Global Rank
-
Country Rank
-
Recent Visits
Traffic Sources
- Social Media:0.48%
- Paid Referrals:0.54%
- Email:0.16%
- Referrals:12.91%
- Search Engines:17.01%
- Direct:68.90%
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Alchemy for ChatGPT Introduction Alchemy is a powerful framework for building and deploying large language models (LLMs) like ChatGPT. It provides a comprehensive set of tools and resources to streamline the entire LLM development lifecycle, from training to deployment and monitoring. Key Features * Modular Design: Alchemy is built with a modular architecture, allowing developers to easily customize and extend its functionality. * Fine-Tuning Capabilities: Alchemy offers robust fine-tuning capabilities, enabling users to adapt pre-trained LLMs to specific tasks and domains. * Deployment Flexibility: Alchemy supports deployment across various platforms, including cloud, on-premise, and edge devices. * Monitoring and Evaluation: Alchemy provides tools for monitoring LLM performance and evaluating their effectiveness. Benefits * Accelerated Development: Alchemy's modularity and pre-built components significantly reduce development time and effort. * Improved Accuracy: Fine-tuning capabilities allow for higher accuracy and performance on specific tasks. * Scalability and Reliability: Alchemy's deployment flexibility ensures scalability and reliability for diverse applications. * Cost-Effectiveness: Alchemy's efficient resource utilization and streamlined workflows contribute to cost savings. Use Cases Alchemy can be used in a wide range of applications, including: * Chatbots and Conversational AI: * Text Generation and Summarization: * Code Generation and Debugging: * Data Analysis and Insights: * Personalized Learning and Education: Conclusion Alchemy is a powerful and versatile framework that empowers developers to build, deploy, and manage LLMs effectively. Its comprehensive features, benefits, and diverse use cases make it an ideal choice for organizations looking to leverage the transformative potential of LLMs.
Alchemy for ChatGPT Introduction Alchemy is a powerful framework for building and deploying large language models (LLMs) like ChatGPT. It provides a comprehensive set of tools and resources to streamline the entire LLM development lifecycle, from training to deployment and monitoring. Key Features * Modular Design: Alchemy is built with a modular architecture, allowing developers to easily customize and extend its functionality. * Fine-Tuning Capabilities: Alchemy offers robust fine-tuning capabilities, enabling users to adapt pre-trained LLMs to specific tasks and domains. * Deployment Flexibility: Alchemy supports deployment across various platforms, including cloud, on-premise, and edge devices. * Monitoring and Evaluation: Alchemy provides tools for monitoring LLM performance and evaluating their effectiveness. Benefits * Accelerated Development: Alchemy's modularity and pre-built components significantly reduce development time and effort. * Improved Accuracy: Fine-tuning capabilities allow for higher accuracy and performance on specific tasks. * Scalability and Reliability: Alchemy's deployment flexibility ensures scalability and reliability for diverse applications. * Cost-Effectiveness: Alchemy's efficient resource utilization and streamlined workflows contribute to cost savings. Use Cases Alchemy can be used in a wide range of applications, including: * Chatbots and Conversational AI: * Text Generation and Summarization: * Code Generation and Debugging: * Data Analysis and Insights: * Personalized Learning and Education: Conclusion Alchemy is a powerful and versatile framework that empowers developers to build, deploy, and manage LLMs effectively. Its comprehensive features, benefits, and diverse use cases make it an ideal choice for organizations looking to leverage the transformative potential of LLMs.Unlock the full capabilities of ChatGPT.
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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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Sketch2Code GPT4-128K GPT4-Vision - Sidebar This is a simple sidebar for a Sketch2Code application powered by GPT4-128K and GPT4-Vision. It likely contains: * Upload Sketch: A button or area to upload an image sketch. * Code Generation Options: Settings to choose the programming language, desired code complexity, or other generation parameters. * Output Code: A display area to show the generated code. * Clear Output: A button to clear the generated code. Let me know if you'd like me to elaborate on any specific aspect of the sidebar!
Sketch2Code GPT4-128K GPT4-Vision - Sidebar This is a simple sidebar for a Sketch2Code application powered by GPT4-128K and GPT4-Vision. It likely contains: * Upload Sketch: A button or area to upload an image sketch. * Code Generation Options: Settings to choose the programming language, desired code complexity, or other generation parameters. * Output Code: A display area to show the generated code. * Clear Output: A button to clear the generated code. Let me know if you'd like me to elaborate on any specific aspect of the sidebar!Sketch2Code GPT4-128K GPT4-Vision - FREE
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Delegate applying to jobs to your assistants or use AI Copilot Applying to jobs can be a tedious and time-consuming task. Delegate this task to your assistants and let them handle the initial application process, including resume submission and cover letter writing. Alternatively, utilize AI Copilot, an innovative tool that can automate the job application process, saving you time and energy. By delegating or automating this task, you can focus on more important things, such as preparing for interviews, networking, and building meaningful connections in your industry. This approach can also increase your chances of getting hired, as your assistants or AI Copilot can help you apply to more job openings, thereby increasing your visibility and reach. Remember, time is valuable, and by delegating or automating the job application process, you can make the most of your time and achieve your career goals more efficiently.
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