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DeeperML

Harsh Mishra@Analytics Vidhya //
DeepSeek AI has been making significant contributions to the open-source community, particularly in the realm of AI model efficiency and accessibility. They recently launched the Fire-Flyer File System (3FS), a high-performance distributed file system tailored for AI training and inference workloads. This system is designed to address the challenges of managing large-scale, concurrent data access, a common bottleneck in traditional file systems. 3FS leverages modern SSDs and RDMA networks, offering a shared storage layer that facilitates the development of distributed applications by bypassing limitations seen in more traditional, locality-dependent file systems.

DeepSeek's commitment extends to data processing and model optimization. They have introduced the Smallpond framework for data processing and released quantized DeepSeek-R1 models, optimized for deployment-ready reasoning tasks. The quantized models, including Llama-8B, Llama-70B, Qwen-1.5B, Qwen-7B, Qwen-14B, and Qwen-32B, are available as a Hugging Face collection with evaluations, benchmarks, and setup instructions. These models maintain competitive reasoning accuracy while unlocking significant inference speedups.

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References :
  • Analytics Vidhya: DeepSeek #OpenSourceWeek Day 5: Launch of 3FS and Smallpond Framework
  • MarkTechPost: DeepSeek AI Releases Fire-Flyer File System (3FS): A High-Performance Distributed File System Designed to Address the Challenges of AI Training and Inference Workload
  • Neural Magic: Quantized DeepSeek-R1 Models: Deployment-Ready Reasoning Models
  • MarkTechPost: DeepSeek AI Releases Smallpond: A Lightweight Data Processing Framework Built on DuckDB and 3FS
  • www.itpro.com: ‘Awesome for the community’: DeepSeek open sourced its code repositories, and experts think it could give competitors a scare
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