Csaba Kecskemeti PRO
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(I believe it has overthinking it a bit :) )
https://youtu.be/Iqu5s9aFaXA?si=QWZe293iTKf_3ELU
DevQuasar/deepseek-ai.DeepSeek-R1-0528-GGUF

https://youtu.be/4F8g_LThli0?si=MGba2SUTHt6xYw3T
Quants uploading now
Big thanks to @ngxson !

Quants DevQuasar/meta-llama.Llama-4-Scout-17B-16E-Instruct-GGUF

The system varies (different motherboard and CPU ... but that probably that has little effect on the inference performance).
https://devquasar.com/gpu-gguf-inference-comparison/
the exact models user are in the page
I'd welcome results from other GPUs is you have access do anything else you've need in the post. Hopefully this is useful information everyone.

| 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/

Follow-up
With the smaller context length dataset the training has succeeded.

nvidia/Llama-3_3-Nemotron-Super-49B-v1
GGUFs:
DevQuasar/nvidia.Llama-3_3-Nemotron-Super-49B-v1-GGUF
Enjoy!

DevQuasar/CohereForAI.c4ai-command-a-03-2025-GGUF
6.7t/s on a 3gpu setup (4080 + 2x3090)
(q3, q4 currently uploading)

No success so far, the training data contains some larger contexts and it fails just before complete the first epoch.
(dataset: DevQuasar/brainstorm-v3.1_vicnua_1k)
If anyone has further suggestion to the bnb config (with ROCm on MI100)?
bnb_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_use_double_quant=True,
bnb_4bit_compute_dtype=torch.bfloat16
)
Now testing with my other dataset that is smaller seems I have a lower memory need
DevQuasar/brainstorm_vicuna_1k

It's failed by the morning, need to find more room to decrease the memory



Updated the post with GGUF (Q4,Q8) performance metrics

Good callout will add this evening
Llama 3 8b q8 was around 80t/s generation

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.

@sometimesanotion you might have more experience with AMD than me :)

So far I'm managed to have a working bnb up:
(bnbtest) kecso@gpu-testbench2:~/bitsandbytes/examples$ python -m bitsandbytes
g++ (Ubuntu 14.2.0-4ubuntu2) 14.2.0
Copyright (C) 2024 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
++++++++++++++++++ BUG REPORT INFORMATION ++++++++++++++++++
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
++++++++++++++++++++++++++ OTHER +++++++++++++++++++++++++++
ROCm specs: rocm_version_string='63', rocm_version_tuple=(6, 3)
PyTorch settings found: ROCM_VERSION=63
The directory listed in your path is found to be non-existent: local/gpu-testbench2
The directory listed in your path is found to be non-existent: @/tmp/.ICE-unix/2803,unix/gpu-testbench2
The directory listed in your path is found to be non-existent: /etc/xdg/xdg-ubuntu
The directory listed in your path is found to be non-existent: /org/gnome/Terminal/screen/6bd83ab2_fd9f_4990_876a_527ef8117ef6
The directory listed in your path is found to be non-existent: //debuginfod.ubuntu.com
WARNING! ROCm runtime files not found in any environmental path.
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
++++++++++++++++++++++ DEBUG INFO END ++++++++++++++++++++++
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Checking that the library is importable and ROCm is callable...
SUCCESS!
Installation was successful!
It's able to load the model to vram, but inference fails:
Exception: cublasLt ran into an error!
This is the main problem with anything not NVIDIA. The software is painful!
Keep trying...