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bastefaniak

PROFILE

Bastefaniak

Over a two-month period, this developer contributed to both the nvidia-cosmos/cosmos-rl and vllm-project/vllm-omni repositories, focusing on deep learning and GPU programming with Python. They enhanced Cosmos3 by integrating action modality and policy support, enabling action-driven predictions and forward dynamics within a multimodal framework. In nvidia-cosmos/cosmos-rl, they improved hardware compatibility by disabling DeepEP on legacy GPUs and corrected MoE routing logic for DeepseekV3 and Qwen3, reducing edge-case failures and improving model efficiency. Their work demonstrated expertise in model optimization, computer vision, and collaborative feature delivery, addressing both deployment flexibility and stability across diverse GPU architectures.

Overall Statistics

Feature vs Bugs

67%Features

Repository Contributions

3Total
Bugs
1
Commits
3
Features
2
Lines of code
1,434
Activity Months2

Work History

June 2026

1 Commits • 1 Features

Jun 1, 2026

June 2026 performance summary: Delivered Cosmos3 Action Modality and Policy Support for vllm-omni, enabling action generation and forward dynamics, integration of action data into the multimodal framework, and action policies to guide autonomous and interactive tasks. No major bugs fixed this month. This work expands the product's capabilities for action-enabled multimodal workflows, improving deployment flexibility and user outcomes. Key tech skills demonstrated include multimodal modeling, action modality, policy integration, forward dynamics, and collaborative code contributions.

December 2025

2 Commits • 1 Features

Dec 1, 2025

December 2025 (nvidia-cosmos/cosmos-rl): Key features delivered and bugs fixed with a focus on hardware compatibility and MoE reliability. Achieved stability for legacy GPUs by disabling DeepEP on architectures older than Hopper, and corrected MoE routing by fixing n_local_experts computation for DeepseekV3 and Qwen3. These changes reduce edge-case failures, improve performance and efficiency, and support broader deployment across GPU architectures.

Activity

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Quality Metrics

Correctness93.4%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage40.0%

Skills & Technologies

Programming Languages

Python

Technical Skills

Computer VisionDeep LearningGPU programmingMachine LearningPythondeep learningmachine learningmodel optimization

Repositories Contributed To

2 repos

Overview of all repositories you've contributed to across your timeline

nvidia-cosmos/cosmos-rl

Dec 2025 Dec 2025
1 Month active

Languages Used

Python

Technical Skills

Deep LearningGPU programmingPythondeep learningmachine learningmodel optimization

vllm-project/vllm-omni

Jun 2026 Jun 2026
1 Month active

Languages Used

Python

Technical Skills

Computer VisionDeep LearningMachine LearningPython