This is the Linux app named CrypTen whose latest release can be downloaded as CrypTenv0.1sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named CrypTen with OnWorks for free.
इस ऐप को चलाने के लिए इन निर्देशों का पालन करें:
- 1. इस एप्लिकेशन को अपने पीसी में डाउनलोड करें।
- 2. हमारे फ़ाइल प्रबंधक में https://www.onworks.net/myfiles.php?username=XXXXX उस उपयोगकर्ता नाम के साथ दर्ज करें जो आप चाहते हैं।
- 3. इस एप्लिकेशन को ऐसे फाइल मैनेजर में अपलोड करें।
- 4. इस वेबसाइट से ऑनवर्क्स लिनक्स ऑनलाइन या विंडोज ऑनलाइन एमुलेटर या मैकोज़ ऑनलाइन एमुलेटर शुरू करें।
- 5. ऑनवर्क्स लिनक्स ओएस से आपने अभी शुरुआत की है, हमारे फाइल मैनेजर को https://www.onworks.net/myfiles.php?username=XXXXX उस यूजरनेम के साथ जाएं जो आप चाहते हैं।
- 6. एप्लिकेशन डाउनलोड करें, इसे इंस्टॉल करें और इसे चलाएं।
स्क्रीनशॉट
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क्रिप्टेन
वर्णन
CrypTen is a research framework developed by Facebook Research for privacy-preserving machine learning built directly on top of PyTorch. It provides a secure and intuitive environment for performing computations on encrypted data using Secure Multiparty Computation (SMPC). Designed to make secure computation accessible to machine learning practitioners, CrypTen introduces a CrypTensor object that behaves like a regular PyTorch tensor, allowing users to seamlessly apply automatic differentiation and neural network operations. Its design mirrors PyTorch’s modular and library-based structure, enabling flexible experimentation, debugging, and model development. The framework supports both encryption and decryption of tensors and operations such as addition and multiplication over encrypted values. Although not yet production-ready, CrypTen focuses on advancing real-world secure ML applications, such as training and inference over private datasets, without exposing sensitive data.
विशेषताएं
- Implements privacy-preserving machine learning using Secure Multiparty Computation
- Provides CrypTensor, a PyTorch-like encrypted tensor supporting autograd and modules
- Enables encrypted model training and inference with minimal code changes
- Offers rich tutorials and examples for encrypted neural networks and models
- Supports GPU acceleration for efficient encrypted computation
- Focused on research use cases and extensible for experimental privacy applications
प्रोग्रामिंग भाषा
जावास्क्रिप्ट, पायथन
श्रेणियाँ
This is an application that can also be fetched from https://sourceforge.net/projects/crypten.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
