Forwarded from KerVerse
Hi everyone! 🎉🤖 As you know, I love to explore and experiment with new technologies. Recently, I've been working with a coding copilot AI(RUNNING 100% LOCALLY) and let me tell you, it's pretty awesome! 😎 This AI is great at writing whole models and making all sorts of things happen in the background. It's like having a superpower at your fingertips! 💪
I know what you're thinking - "wow, that sounds amazing!" And you're right, it is! But don't just take my word for it - check out the demo websiteit I created using just the telegram channel bio💀! Seemed like a great way to get a glimpse of how good it is🤷♂️
I hope you enjoy exploring and experimenting with this new technology as much as I have. Stay tuned for more on this topic!
#AI #LLMs #Copilot
@dotnetWarrior
I know what you're thinking - "wow, that sounds amazing!" And you're right, it is! But don't just take my word for it - check out the demo website
I hope you enjoy exploring and experimenting with this new technology as much as I have. Stay tuned for more on this topic!
#AI #LLMs #Copilot
@dotnetWarrior
100 LLM Papers to explore (1).zip
166.1 MB
100 LLM Papers to explore
This curated collection comprises 100 papers that delve into the world of Large Language Models (LLMs). If you're an enthusiast, researcher, or simply someone looking to explore developments in the field of language models, this dataset is a treasure trove.
The papers in this dataset cover a wide range of topics within the LLM domain, from the foundational Transformer architectures to advanced techniques in model compression, activation functions, pruning, quantization, normalization, sparsity, fine-tuning, sampling, scaling, mixture of experts, watermarking, and much more.
#Papers #LLMs
@Dagmawi_Babi
This curated collection comprises 100 papers that delve into the world of Large Language Models (LLMs). If you're an enthusiast, researcher, or simply someone looking to explore developments in the field of language models, this dataset is a treasure trove.
The papers in this dataset cover a wide range of topics within the LLM domain, from the foundational Transformer architectures to advanced techniques in model compression, activation functions, pruning, quantization, normalization, sparsity, fine-tuning, sampling, scaling, mixture of experts, watermarking, and much more.
#Papers #LLMs
@Dagmawi_Babi