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[Feature request] Implement 8-bit GPT-J #5

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pablogranolabar opened this issue Nov 13, 2022 · 0 comments · Fixed by #27
Closed

[Feature request] Implement 8-bit GPT-J #5

pablogranolabar opened this issue Nov 13, 2022 · 0 comments · Fixed by #27
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enhancement New feature or request

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@pablogranolabar
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Results in ~11Gb weights vs. 16Gb, implemented in PyTorch now as load_in_8bit=True:

https://huggingface.co/hivemind/gpt-j-6B-8bit
@ggerganov ggerganov added the enhancement New feature or request label Nov 14, 2022
@ggerganov ggerganov mentioned this issue Feb 26, 2023
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@katsu560 katsu560 mentioned this issue Mar 18, 2023
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CCLDArjun pushed a commit to CCLDArjun/ggml that referenced this issue Dec 18, 2023
@SlyEcho @YellowRoseCx
@ardfork @funnbot @Engininja2 @KerfuffleV2 @jammm @jdecourval
ROCm Port (#1087)
6bbc598 
* use hipblas based on cublas
* Update Makefile for the Cuda kernels
* Expand arch list and make it overrideable
* Fix multi GPU on multiple amd architectures with rocblas_initialize() (ggerganov#5)
* add hipBLAS to README
* new build arg LLAMA_CUDA_MMQ_Y
* fix half2 decomposition
* Add intrinsics polyfills for AMD
* AMD assembly optimized __dp4a
* Allow overriding CC_TURING
* use "ROCm" instead of "CUDA"
* ignore all build dirs
* Add Dockerfiles
* fix llama-bench
* fix -nommq help for non CUDA/HIP

---------

Co-authored-by: YellowRoseCx <[email protected]>
Co-authored-by: ardfork <[email protected]>
Co-authored-by: funnbot <[email protected]>
Co-authored-by: Engininja2 <[email protected]>
Co-authored-by: Kerfuffle <[email protected]>
Co-authored-by: jammm <[email protected]>
Co-authored-by: jdecourval <[email protected]>
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4-bit Integer quantisation ggerganov/ggml
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@ggerganov @pablogranolabar