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FlexGen reviews and mentions
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Training LLaMA-65B with Stanford Code
#1: Progress Update | 4 comments #2: the default UI on the pinned Google Colab is buggy so I made my own frontend - YAFFOA. | 18 comments #3: Paper reduces resource requirement of a 175B model down to 16GB GPU | 19 comments
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Replika users fell in love with their AI chatbot companions. Then they lost them
It's really just a gpu vram limitation: affordable GPUs are rather memory starved.
Fortunately people have started writing implementations for pipelining across multiple gpus.
https://github.com/Ying1123/FlexGen
- Same as with Stable Diffusion, new AI based LAION, are coming up slowly but surely: Paper reduces resource requirement of a 175B model down to 16GB GPU
- And Here..We..Go: Running large language models like ChatGPTon a single GPU. Up to 100x faster than other offloading systems
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When, how and why will this Stable Diffusion spring stop?
Actually there's a solution : read this paper https://github.com/Ying1123/FlexGen/blob/main/docs/paper.pdf
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Exciting new shit.
Flexgen - Run big models on your small GPU https://github.com/Ying1123/FlexGen
- Paper reduces resource requirement of a 175B model down to 16GB GPU
- FlexGen - Run 175B Parameter Models on consumer hardware
- Running large language models like ChatGPT on a single GPU
- FlexGen: Running large language models like ChatGPT/GPT-3/OPT-175B on a single GPU
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A note from our sponsor - InfluxDB
www.influxdata.com | 25 Apr 2024
Stats
Ying1123/FlexGen is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of FlexGen is Python.
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