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fuzzy-mittenz  updated a collection 3 days ago
Project-Jormungandr
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SotA-GGUF
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SotA
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IntelligentEstate's activity

takarajordan 
posted an update 10 days ago
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🎌 Two months in, https://github.com/takara-ai/go-attention has passed 429 stars on GitHub.

We built this library at takara.ai to bring attention mechanisms and transformer layers to Go — in a form that's lightweight, clean, and dependency-free.

We’re proud to say that every part of this project reflects what we set out to do.

- Pure Go — no external dependencies, built entirely on the Go standard library
- Core support for DotProductAttention and MultiHeadAttention
- Full transformer layers with LayerNorm, feed-forward networks, and residual connections
- Designed for edge, embedded, and real-time environments where simplicity and performance matter

Thank you to everyone who has supported this so far — the stars, forks, and feedback mean a lot.
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csabakecskemeti 
posted an update 10 days ago
csabakecskemeti 
posted an update 11 days ago
takarajordan 
posted an update 16 days ago
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1556
AI research over coffee ☕️
No abstracts, just bullet points.
Start your day here: https://tldr.takara.ai
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takarajordan 
posted an update 25 days ago
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Takara takes 3rd place in the {tech:munich} AI hackathon with Fudeno!

A little over 2 weeks ago @aldigobbler and I set out to create the largest MultiModal SVG dataset ever created, we succeeded in this and when I was in Munich, Germany I took it one step further and made an entire app with it!

We fine-tuned Mistral Small, made a Next.JS application and blew some minds, taking 3rd place out of over 100 hackers. So cool!

If you want to see the dataset, please see below.

takara-ai/fudeno-instruct-4M
csabakecskemeti 
posted an update 26 days ago
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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.
csabakecskemeti 
posted an update 28 days ago
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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/
csabakecskemeti 
posted an update about 1 month ago