This is the Windows app named Kimi Linear whose latest release can be downloaded as Kimi-Linearsourcecode.zip. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Kimi Linear 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
Kimi Linear
DESCRIPTION
Kimi Linear is a hybrid linear attention architecture developed for efficient language modeling across short, long-context, and reinforcement learning workloads. Its core mechanism, Kimi Delta Attention, refines the gated delta rule with fine-grained controls for managing finite-state recurrent memory. The architecture combines KDA and global Multi-head Latent Attention layers at a 3:1 ratio to preserve model quality while reducing memory demands. Released Base and Instruct checkpoints contain 48 billion total parameters, activate 3 billion parameters per token, and support contexts up to one million tokens. The models were trained on 5.7 trillion tokens and can reduce KV cache requirements by up to 75 percent. Kimi Linear supports inference through Hugging Face Transformers and deployment as an OpenAI-compatible API with vLLM.
Features
- Kimi Delta Attention mechanism
- Hybrid KDA and MLA architecture
- One-million-token context support
- 48B parameters with 3B activated
- Reduced KV cache requirements
- Transformers and vLLM deployment
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/kimi-linear.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
