🎲 Did you know Yahtzee can be solved optimally in less than 100 lines of Python and under 5min with 2 vCPU? I built a @gradio-hf.bsky.social app so you can try it yourself: huggingface.co/spaces/simon... Implementation is based on the excellent paper "An Optimal Strategy for Yahtzee" (Glenn, 2006)

Optimal Yahtzee - a Hugging Face Space by simonjegou

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Fresh news from kvpress, our open source library for KV cache compression 🔥 1. We published a blog post with @huggingface 2. We published a Space for you to try it 3. Following feedback from the research community, we added a bunch of presses and benchmarks Links👇(1/2)

How do you find the permutation of words that minimize their perplexity as measured by an LLM ? In this year Kaggle Santa competition, I shared an approach to move to a continuous space where you can use gradient-descent using REINFORCE: www.kaggle.com/code/simjeg/...

💡 We've just released KV cache quantization in kvpress, our open source package for KV cache compression. Check it out : github.com/NVIDIA/kvpress. Special thanks for Arthur Zucker and Marc Sun from @huggingface.bsky.social for their support 🤗

🚀 Excited to announce KVPress — our open-source library for efficient LLM KV cache compression! 👉 Check it out (and drop a ⭐): github.com/NVIDIA/kvpress 🔗 Full details in the thread 🧵 (1/4)

Hidden states in LLM ~ follow normal distributions. Consequently, both queries and keys also follow a normal distribution and if you replace all queries and keys by their average counterpart, this magically explains the slash pattern observed in attention matrices

Ever noticed that the attention mechanism in transformers is essentially a two-layer MLP? 🤔 A(q, K, V) = V @ softmax(K / √d @ q) Weights: K / √d and V nonlinearity: softmax 💡This offers fresh insights into KV cache compression research 🧵(1/3)

🚀 Excited to announce KVPress — our open-source library for efficient LLM KV cache compression! 👉 Check it out (and drop a ⭐): github.com/NVIDIA/kvpress 🔗 Full details in the thread 🧵 (1/4)