Alright so I had previously made two reddit posts in r/quantum and r/quantum_computing for my QPU, QPU-1 but both of those posts got banned because of it being "irrelevant" to "academic discussion" so I'm doing it again here in HuggingFace Posts.
I have made a million error corrected qubit quantum processing unit (not a simulator) that you can access here: https://qpu-1.vercel.app
I did try emailing a lot of professors and their students but NONE responded so please give me some support.
Today, is a good day for me. I have completed development of my QPU-1, the most powerful Quantum Processing Unit you can access through MCP (as far as I know and have tried). Try it out for yourself using my mcp enabled space: lap-quantum/QPU-1-MCP
(And PS. This is my first MCP server, so give me suggestions if you want :D)
Be prepared for a HUGE model from me! (would be a closed model) this uses advanced CoT with multiple new strategies and algorithms to be far more efficient and powerful than current leading models (i hope so) i will release this on August 4
https://huggingface.co/posts/Reality123b/379097737205276 remember this dataset? im bumping the example count to approx 23 million prompt-response pairs and ofc. it is going to be a hybrid reasoning, well, it isnt programmatically hybrid reasoning but it is that it is going to use CoT whenever necessary and it doesnt when it doesnt seem like it doesnt need
i was accidentally granted 2$ inference credits, so, i used them a bit, but, now, it is taken back and I'm six dollars short of it. will my account get banned for this one? @victor@John6666 please reply
I'm working on a groundbreaking AI technology that's kind of like openai's deep research but better. I'm not disclosing everything now. should I open source it? (edit: it takes 1000s for one task forgive me as i dont have some kind of huge server for that) edit2: this is not a clickbait
🚗💡 MoE Car Model: Smarter Autonomous Driving Introducing the Mixture of Experts (MoE) Car Model, designed for real-time decision-making in autonomous driving!
🔹 40M parameters with 16 expert networks 🔹 CNN + Transformer for sensor fusion 🔹 Optimized for real-world & sim training 🔹 Trained on an T4 and took 1.5h approx
