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" alt="Launch chronos-2 on AMD/Nvidia GPU Direct EXE Setup" style="display:block; width:100%; height:auto; border-radius:8px;">
The shortest path to running this model is by activating Hyper-V features.
Please follow the instructions listed below to get started.
The download manager will automatically pull several gigabytes of data.
Without any user input, the software calibrates parameters for optimal hardware usage.
|
📎 HASH: a6cc7340ebe675cb2b624fd5eb9e110b | Updated: 2026-07-13
|
At the forefront of artificial intelligence, chronos-2 represents a groundbreaking leap forward in language model design. By harnessing the power of novel attention mechanisms and incorporating a built-in reinforcement learning loop, this cutting-edge technology promises to revolutionize the way we interact with complex sequential tasks. With unparalleled precision and accuracy, chronos-2 is poised to redefine the boundaries of temporal reasoning and real-time processing. This innovative approach has been meticulously crafted to tackle even the most daunting challenges, making it an indispensable tool for researchers, developers, and problem-solvers alike.
- By leveraging a custom-designed neural network architecture, chronos-2 is able to efficiently process vast amounts of data and adapt to emerging trends in various fields.
- The model’s unique attention mechanism allows it to dynamically weigh past and future context, enabling it to make predictions with unprecedented accuracy.
- Through its reinforcement learning loop, chronos-2 can refine its predictions based on user feedback, making it a highly adaptable and responsive tool for evolving scenarios.
| Key Performance Metrics for Chronos-2 | |||
|---|---|---|---|
| Parameter Count (B) | 12,000,000,000 | 8,000,000,000 | 15,000,000,000 |
| Inference Latency (ms) | 23 | 35 | 28 |
| Benchmark Score (%) | 94.7 | 89.2 | 92.5 |
Frequently Asked Questions
- What inspired the development of chronos-2?
- A unique blend of academic research and real-world applications led to the creation of this innovative language model.
- How does chronos-2’s reinforcement learning loop work?
- The built-in loop continuously refines predictions based on user feedback, enabling the model to adapt to changing environments.
As we continue to push the boundaries of artificial intelligence, it’s clear that chronos-2 represents a pivotal moment in our journey towards more accurate and efficient language processing. With its unparalleled precision and adaptability, this cutting-edge technology is poised to revolutionize the way we approach complex sequential tasks.
- Downloader pulling custom frame-interpolation models for local Stable Video Diffusion pipeline architectures
- How to Launch chronos-2 Full Method
- Setup tool initializing prefix-caching parameters inside production-tier vLLM clusters
- Launch chronos-2 Using Pinokio Full Speed NPU Mode FREE
- Downloader pulling specialized cyber-security and log-parsing local models
- chronos-2 on Copilot+ PC For Beginners FREE
- Installer pre-configuring modern machine learning dependency matrices on local desktop computer systems
- Zero-Click Run chronos-2 No Admin Rights FREE