Video Analysis and Generation via a Semantic Progress Function
Paper • 2604.22554 • Published • 63
Cedric Perauer
CedricPerauer
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2D/3D Vision
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I found it very funny that the Hugging Face profile has a specific section where we can share our hardware.
It really brings back memories of the good old days when we used to flex our custom PC specs on enthusiast forums 20 years ago! That inspired me to fill out my own profile and share it here.
And this is my first set of GPUs that I am using to learn MLOps:
- RTX 3090 – the best one; unfortunately it doesn't support the latest FP8 and FP4, but it’s still very powerful.
- Tesla V100 – performance is almost like the RTX 3090, just much older.
- Tesla P100 – old, and doesn't have tensor cores, but still can handle small models.
- Radeon MI50 – old, similar to the P100, but uses ROCm instead of CUDA, which is actually a pretty good experience to setup.
- GTX 1080 Ti – mostly useless, no FP16 support.
- GTX 1660 – first generation of the Turing architecture, but mostly useless.
llmlaba
It really brings back memories of the good old days when we used to flex our custom PC specs on enthusiast forums 20 years ago! That inspired me to fill out my own profile and share it here.
And this is my first set of GPUs that I am using to learn MLOps:
- RTX 3090 – the best one; unfortunately it doesn't support the latest FP8 and FP4, but it’s still very powerful.
- Tesla V100 – performance is almost like the RTX 3090, just much older.
- Tesla P100 – old, and doesn't have tensor cores, but still can handle small models.
- Radeon MI50 – old, similar to the P100, but uses ROCm instead of CUDA, which is actually a pretty good experience to setup.
- GTX 1080 Ti – mostly useless, no FP16 support.
- GTX 1660 – first generation of the Turing architecture, but mostly useless.
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