Search Results for "granular" - Page 5
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Showing 113 open source projects for "granular"
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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IdentityTrust is a library that allows you to express trust criteria for identity providers and the attributes that they can assert in a fine granular and customizable way.
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Designed for data centre management, secureStore uses end to end encryption, granular user access control, comprehensive login, and open source technology to create a secure way to manage sensitive information such as private keys, certificates, etc.
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Postfix Policy Server - e-mail administrators assert server-side SPAM/UCE filter control using SQL based white and black lists. Wildcards provide granular control of source user names, domains, and IP addresses on a per recipient basis.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Kasai is a 100% Java based authentication and authorization framework. It allows you to integrate into your application a granular, complete and manageable permission scheme.
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This is an implementation of the Granular Neural Network architecture defined by S. Dick, A. Tappenden, C. Badke, O. Olarewaju. It is provided for the use of the public, and the convenience of researchers who may wish to develop or use this new system.
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Amber is an easy-to-use, multi-faceted granular sampling tool for composers wishing to construct timbrally complex sounds; available as a command-line tool for Linux-similar operating systems, or with a Cocoa wrapper that runs on Macintosh OS X.
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BOBUP - Backup and recovery for application business objects. Backup usually implies backing up files/db - this is non-intuitive. With BOBUP, backup and recover granular info (eg. specific customer) independent of files/db.
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Grain Painter turns a loaded or drawn image into a sound sample for playback or saving using a technique called granular synthesis. The tool can be used to produce unique and unusual synthesized sound samples.
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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GRAnular Media Simulation in C++ using Molecular Dynamics. To be used in PhD work. The code will support: collision, electric dipoles (long range forces), intergranular fluid, and possibly MPI for parallel computing.
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Consistent sample objects (record,play,granular,etc.) for the popular and extendable realtime modular audio environments Max/MSP and pd (pure data).
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Mistral Large 3 675B Instruct 2512
Frontier-scale 675B multimodal instruct MoE model for enterprise AIMis
Mistral Large 3 675B Instruct 2512 is a state-of-the-art multimodal granular Mixture-of-Experts model featuring 675B total parameters and 41B active parameters, trained from scratch on 3,000 H200 GPUs. As the instruct-tuned FP8 variant, it is optimized for reliable instruction following, agentic workflows, production-grade assistants, and long-context enterprise tasks. It incorporates a massive 673B-parameter language MoE backbone and a 2.5B-parameter vision encoder, enabling rich multimodal understanding across text and images. ... -
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Mistral Large 3 675B Instruct 2512 NVFP4
Quantized 675B multimodal instruct model optimized for NVFP4
Mistral Large 3 675B Instruct 2512 NVFP4 is a frontier-scale multimodal Mixture-of-Experts model featuring 675B total parameters and 41B active parameters, trained from scratch on 3,000 H200 GPUs. This NVFP4 checkpoint is a post-training-activation quantized version of the original instruct model, created through a collaboration between Mistral AI, vLLM, and Red Hat using llm-compressor. It retains the same instruction-tuned behavior as the FP8 model, making it ideal for production...
