DevQuasar/ibm-granite.granite-4.0-350m-GGUF
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Open-Source LLMs, Local AI Projects: https://pypi.org/project/llm-predictive-router/
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csabakecskemeti
updated
a
model
about 4 hours ago
csabakecskemeti
published
a
model
about 4 hours ago
csabakecskemeti
updated
a
model
about 4 hours ago
csabakecskemeti
published
a
model
about 4 hours ago
csabakecskemeti
updated
a
model
about 4 hours ago
csabakecskemeti
published
a
model
about 4 hours ago
csabakecskemeti
updated
a
model
about 4 hours ago
csabakecskemeti
published
a
model
about 5 hours ago
csabakecskemeti
updated
a
model
about 17 hours ago
csabakecskemeti
posted
an
update
12 days ago
Post
2490
Christmas came early this year
- 3 replies
csabakecskemeti
posted
an
update
5 months ago
Post
3032
Has anyone ever backed up a model to a sequential tape drive, or I'm the world first? :D
Just played around with my retro PC that has got a tape drive—did it just because I can.
Just played around with my retro PC that has got a tape drive—did it just because I can.
- 5 replies
csabakecskemeti
posted
an
update
5 months ago
Post
464
Deepseek R1 0528 Q2 locally.
(I believe it has overthinking it a bit :) )
https://youtu.be/Iqu5s9aFaXA?si=QWZe293iTKf_3ELU
DevQuasar/deepseek-ai.DeepSeek-R1-0528-GGUF
(I believe it has overthinking it a bit :) )
https://youtu.be/Iqu5s9aFaXA?si=QWZe293iTKf_3ELU
DevQuasar/deepseek-ai.DeepSeek-R1-0528-GGUF
csabakecskemeti
posted
an
update
7 months ago
Post
2110
Local Llama4 Maverick Q2
https://youtu.be/4F8g_LThli0?si=MGba2SUTHt6xYw3T
Quants uploading now
Big thanks to @ngxson !
https://youtu.be/4F8g_LThli0?si=MGba2SUTHt6xYw3T
Quants uploading now
Big thanks to @ngxson !
csabakecskemeti
posted
an
update
7 months ago
Post
1744
Why the 'how many r's in strawberry' prompt "breaks" llama4? :D
Quants DevQuasar/meta-llama.Llama-4-Scout-17B-16E-Instruct-GGUF
Quants DevQuasar/meta-llama.Llama-4-Scout-17B-16E-Instruct-GGUF
- 3 replies
csabakecskemeti
posted
an
update
7 months ago
Post
3407
I'm collecting llama-bench results for inference with a llama 3.1 8B q4 and q8 reference models on varoius GPUs. The results are average of 5 executions.
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.
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.
csabakecskemeti
posted
an
update
7 months ago
Post
2408
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 ± 481.67 |
| llama 8B Q8_0 | 7.95 GiB | 8.03 B | CUDA | 99 | tg128 | 143.18 ± 0.18 |
Comparison with others GPUs
http://devquasar.com/gpu-gguf-inference-comparison/
| llama 8B Q8_0 | 7.95 GiB | 8.03 B | CUDA | 99 | pp512 | 12207.44 ± 481.67 |
| llama 8B Q8_0 | 7.95 GiB | 8.03 B | CUDA | 99 | tg128 | 143.18 ± 0.18 |
Comparison with others GPUs
http://devquasar.com/gpu-gguf-inference-comparison/
csabakecskemeti
posted
an
update
7 months ago
Post
1847
GTC new model announcement now from Nvidia
nvidia/Llama-3_3-Nemotron-Super-49B-v1
GGUFs:
DevQuasar/nvidia.Llama-3_3-Nemotron-Super-49B-v1-GGUF
Enjoy!
nvidia/Llama-3_3-Nemotron-Super-49B-v1
GGUFs:
DevQuasar/nvidia.Llama-3_3-Nemotron-Super-49B-v1-GGUF
Enjoy!
csabakecskemeti
posted
an
update
8 months ago
Post
593
Cohere Command-a Q2 quant
DevQuasar/CohereForAI.c4ai-command-a-03-2025-GGUF
6.7t/s on a 3gpu setup (4080 + 2x3090)
(q3, q4 currently uploading)
DevQuasar/CohereForAI.c4ai-command-a-03-2025-GGUF
6.7t/s on a 3gpu setup (4080 + 2x3090)
(q3, q4 currently uploading)
csabakecskemeti
posted
an
update
8 months ago
Post
843
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
QWQ-32B 4bit QLORA fine tuning
VRAM usage 31.498G/31.984G :D
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- 4 replies
csabakecskemeti
posted
an
update
8 months ago
Post
1998
-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.
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.
-
- 4 replies