This is the Windows app named Thinc whose latest release can be downloaded as v8.2.1_SupportPython3.12.zip. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Thinc with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start any OS OnWorks online emulator from this website, but better Windows online emulator.
- 5. From the OnWorks Windows OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application and install it.
- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.
Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.
SCREENSHOTS
Ad
Thinc
DESCRIPTION
Thinc is a lightweight deep learning library that offers an elegant, type-checked, functional-programming API for composing models, with support for layers defined in other frameworks such as PyTorch, TensorFlow and MXNet. You can use Thinc as an interface layer, a standalone toolkit or a flexible way to develop new models. Previous versions of Thinc have been running quietly in production in thousands of companies, via both spaCy and Prodigy. We wrote the new version to let users compose, configure and deploy custom models built with their favorite framework. Switch between PyTorch, TensorFlow and MXNet models without changing your application, or even create mutant hybrids using zero-copy array interchange. Develop faster and catch bugs sooner with sophisticated type checking. Trying to pass a 1-dimensional array into a model that expects two dimensions? That’s a type error. Your editor can pick it up as the code leaves your fingers.
Features
- Type-check your model definitions with custom types and mypy plugin
- Wrap PyTorch, TensorFlow and MXNet models for use in your network
- Concise functional-programming approach to model definition, using composition rather than inheritance
- Optional custom infix notation via operator overloading
- Integrated config system to describe trees of objects and hyperparameters
- Choice of extensible backends
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/thinc.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
