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I would like to provision compute (servers), gpus (say 2 A100 80GB or H100), storage and network (may be 100GbE) to run OpenApaca 7B (https://huggingface.co/openlm-research/open_llama_7b) model.

How do I go about sizing this? AWS/GCP cluster sizing is okay too.

techele
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  • Zac, it does not. – techele Jun 13 '23 at 20:59
  • So this model has 1 trillion tokens, say ~100GB disk space (it is actually less), however for sake of argument let ~1TB with redundancy etc. Now I need to run some containerized neural net code (what is preferred containers or bare metal) 1. What should be the type of CPU, RAM, GPU for each node? 2. How many containers per node? 3. How many such nodes? 4. What about HA, DP and DR in this case? 5. How much time (expected) for model to train? 6. What could be typical response time for inferencing? 7. Network considerations? 8. How will this model scale? – techele Jun 13 '23 at 21:07
  • The linked canonical answer is that YOU have to benchmark YOUR code (even if it's not code you wrote, it's the code you chose). Hopefully the creator of this package has some sizing guidelines, or will be responsive to you reaching out with these questions. No one here is likely to have a ready answer for you. – mfinni Jun 15 '23 at 01:47
  • There's SOME anecdata in the comments on this thread. You're going to have to do your own research on this one. https://news.ycombinator.com/item?id=35798888 – mfinni Jun 15 '23 at 01:51

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