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On this auspicious occasion of Guru Gobind Singh Jayanti, let us reflect on the teachings of the 10th Sikh Guru, who stood for righteousness, equality, and courage. May his wisdom inspire us to lead a life of compassion, selflessness, and devotion to truth.
Wishing you and your loved ones a blessed Guru Gobind Singh Jayanti filled with spiritual growth and harmony.

Happy Makar Sankranti! May the vibrant kites of joy and prosperity fill your skies, and the warmth of the sun bring success and positivity to your life.

Wishing all students from OptimalXAI a joyous and prosperous Lohri celebration! May this festival bring warmth, happiness, and success to your journey.

As we commemorate Swami Vivekananda’s birthday, OptimalXAI wishes aspiring AI professionals a fulfilling and successful journey. May Swamiji’s ideals guide you towards innovation, knowledge, and excellence. Happy !

Hi AI Aspirants,

Wishing all of you a joyous and successful New Year 2024! May this year be filled with growth, learning, and achievement. Your journey with OptimalXAI is set to be even more inspiring. Cheers to a fantastic year ahead!!!

Devvrat Rana,
Founder of OptimalXAI.

Wishing all the students at OptimalXAI a joyous Christmas filled with warmth, laughter, and well-deserved rest. May the holiday season inspire creativity and bring you moments of relaxation before the new academic challenges ahead. Merry Christmas!

🇮🇳 Celebrating the indomitable spirit and valor of the Indian Navy on ! Saluting the guardians of our seas, whose commitment and sacrifice protect our nation's maritime borders. 🌊⚓

Unlocking the Potential of Language Models: Streamlining Text Generation Challenges with StreamingLLM

Navigating the complexities of infinite-length text with Language Models (LLMs) poses unique challenges. Storing extensive Key and Value (KV) states demands substantial memory, and models may encounter difficulties generating text beyond their training sequence length. StreamingLLM tackles this by preserving only the latest tokens and attention sinks, discarding intermediate tokens. This empowers the model to produce coherent text from recent tokens without requiring a cache reset—a capability not present in previous methodologies.

GitHub - mit-han-lab/streaming-llm: Efficient Streaming Language Models with Attention Sinks Efficient Streaming Language Models with Attention Sinks - GitHub - mit-han-lab/streaming-llm: Efficient Streaming Language Models with Attention Sinks

Unlocking the Potential of Language Models: Streamlining Text Generation Challenges with StreamingLLM

Navigating the complexities of infinite-length text with Language Models (LLMs) poses unique challenges. Storing extensive Key and Value (KV) states demands substantial memory, and models may encounter difficulties generating text beyond their training sequence length. StreamingLLM tackles this by preserving only the latest tokens and attention sinks, discarding intermediate tokens. This empowers the model to produce coherent text from recent tokens without requiring a cache reset—a capability not present in previous methodologies.

https://github.com/mit-han-lab/streaming-llm

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