#DeepSeek models are open-weight, letting anyone build on top of them. Interesting to note that the community focused on quantized versions for better efficiency & accessibility. They want models that use less #memory, run #faster, and are more #energy-efficient.

The Impact of DeepSeek R1's Release:

Initial Launch: DeepSeek R1 introduced 8 models, garnering 540,000 downloads, setting a strong foundation.
Community Response: Within just one week, the community transformed these open-weight models into over 550 new varieties on Hugging Face, with total downloads reaching 2.5 million, nearly five times that of the initial release.

Key Insights:

Open-Weight Advantage: The accessibility of DeepSeek's models as open-weight allowed for widespread innovation and adaptation by users.
Focus on Efficiency: The community's efforts were notably directed towards creating quantized versions, optimizing for lower memory usage, faster processing, and energy efficiency, highlighting a demand for practical, resource-conscious AI solutions.

DeepSeek's: Happy #Engineers for #Customer Satisfaction🚀

AI models should be open-source.