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Pushing This AI Beast To Its Limit (2x RTX 6000)🔥

Matthew Berman2024-06-20
ai#llm#artificial intelligence#large language model#dell#nvidia#rtx6000
19K views|1 months ago
💫 Short Summary

The video showcases a powerful Dell and Nvidia Precision 5860 Tower workstation ideal for data scientists, with a chance to win hardware. Testing different models on the GPU shows impressive speeds and utilization levels. Issues arise when attempting to write a snake game in Python. Fucus is demonstrated for text to image conversion with efficient results. The creator plans to continue testing performance and offers a giveaway for a Dell monitor. Viewers are encouraged to like, subscribe, and stay tuned for future content.

✨ Highlights
📊 Transcript
Dell and Nvidia Precision 5860 Tower workstation with top-of-the-line specifications.
00:41
The system includes dual Nvidia RTX 6000 GPUs, 128GB of RAM, and 4TB of SSD storage.
Ideal for data scientists and running massive local models at high speeds.
Limitations of running unquantized models on GPUs due to VRAM constraints.
Demonstrates the use of quantization techniques to optimize model performance.
Testing of different models on GPU for speed and efficiency.
06:04
GPU utilization remains around 40-50%, with speeds of 60 tokens per second.
Speed slightly decreases as models get larger but remains fast.
Experiment maxes out at running 10 models simultaneously, utilizing 56.84 GB of VRAM out of 96 GB available.
Segment concludes with testing Q8 quantization for loading capacity and VRAM usage per model.
Testing various models on a machine with 96 GB of memory and encountering issues with GPU utilization and token per second rates.
10:58
Attempting to write a snake game in Python using pi game, facing challenges with undefined variables.
Despite using a powerful model, unable to successfully create the game.
Exploring the speed of text to image conversion using Fucus for stable diffusion.
Highlights of Fucus Installation Demonstration:
12:26
Installation of Fucus for running diffusion models locally is shown to be quick and easy.
Results are generated in just 4 seconds per image, highlighting the efficiency of the process.
Creator plans to further test performance on their main PC and welcomes suggestions for pushing its limits.
Viewers have the chance to win a Dell monitor by signing up for the creator's newsletter, with a call to action to like, subscribe, and stay tuned for future content at the end of the video.