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Open-Source LLMs, Local AI Projects: https://pypi.org/project/llm-predictive-router/

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csabakecskemetiย 
posted an update 1 day ago
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1773
Managed to get my hands on a 5090FE, it's beefy

| llama 8B Q8_0 | 7.95 GiB | 8.03 B | CUDA | 99 | pp512 | 12207.44 ยฑ 481.67 |
| llama 8B Q8_0 | 7.95 GiB | 8.03 B | CUDA | 99 | tg128 | 143.18 ยฑ 0.18 |

Comparison with others GPUs
http://devquasar.com/gpu-gguf-inference-comparison/
csabakecskemetiย 
posted an update 5 days ago
csabakecskemetiย 
posted an update 10 days ago
csabakecskemetiย 
posted an update 16 days ago
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817
Fine tuning on the edge. Pushing the MI100 to it's limits.
QWQ-32B 4bit QLORA fine tuning
VRAM usage 31.498G/31.984G :D

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csabakecskemetiย 
posted an update 22 days ago
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1948
-UPDATED-
4bit inference is working! The blogpost is updated with code snippet and requirements.txt
https://devquasar.com/uncategorized/all-about-amd-and-rocm/
-UPDATED-
I've played around with an MI100 and ROCm and collected my experience in a blogpost:
https://devquasar.com/uncategorized/all-about-amd-and-rocm/
Unfortunately I've could not make inference or training work with model loaded in 8bit or use BnB, but did everything else and documented my findings.
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csabakecskemetiย 
posted an update 28 days ago
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2769
Testing Training on AMD/ROCm the first time!

I've got my hands on an AMD Instinct MI100. It's about the same price used as a V100 but on paper has more TOPS (V100 14TOPS vs MI100 23TOPS) also the HBM has faster clock so the memory bandwidth is 1.2TB/s.
For quantized inference it's a beast (MI50 was also surprisingly fast)

For LORA training with this quick test I could not make the bnb config works so I'm running the FT on the fill size model.

Will share all the install, setup and setting I've learned in a blog post, together with the cooling shroud 3D design.
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csabakecskemetiย 
posted an update about 1 month ago