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Polaris 4B Preview F32 GGUF
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Polaris 4B Preview F32 GGUF

Developed by prithivMLmods
Polaris is an open-source post-training method that uses reinforcement learning to optimize and enhance the model and improve inference capabilities.
Large Language Model
Transformers
 EnglishOpen Source License:Apache-2.0#Reinforcement learning optimization#High-precision inference#Open-source post-training
Downloads 765
Release Time : 6/21/2025

Model Overview

Polaris optimizes the model through reinforcement learning technology, significantly improving its performance on challenging inference tasks and even surpassing top-tier commercial systems.

Model Features

Reinforcement learning optimization
Use reinforcement learning technology for post-training optimization to significantly improve the model's inference capabilities
Open-source method
Use open-source data and academic-level resources for optimization
Multiple quantization versions
Provide multiple quantization versions from F32 to Q2_K to meet different hardware requirements

Model Capabilities

Handling complex inference tasks
Language understanding and generation
Logical reasoning

Use Cases

Academic research
Solving complex inference tasks
Used to solve academic problems that require advanced inference capabilities
Surpass multiple commercial systems in benchmark tests
Commercial applications
Intelligent decision support
Provide decision support based on advanced inference for enterprises
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