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511 points andy99 | 2 comments | | HN request time: 0.549s | source
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isusmelj ◴[] No.44536509[source]
I hope they do well. AFAIK they’re training or finetuning an older LLaMA model, so performance might lag behind SOTA. But what really matters is that ETH and EPFL get hands-on experience training at scale. From what I’ve heard, the new AI cluster still has teething problems. A lot of people underestimate how tough it is to train models at this scale, especially on your own infra.

Disclaimer: I’m Swiss and studied at ETH. We’ve got the brainpower, but not much large-scale training experience yet. And IMHO, a lot of the “magic” in LLMs is infrastructure-driven.

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lllllm ◴[] No.44539869[source]
No, the model has nothing do to with Llama. We are using our own architecture, and training from scratch. Llama also does not have open training data, and is non-compliant, in contrast to this model.

Source: I'm part of the training team

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1. danielhanchen ◴[] No.44540067[source]
If you guys need help on GGUFs + Unsloth dynamic quants + finetuning support via Unsloth https://github.com/unslothai/unsloth on day 0 / 1, more than happy to help :)
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2. lllllm ◴[] No.44540233[source]
absolutely! i've sent you a linkedin message last week. but here seems to work much better, thanks a lot!