- I think you should be okay. I've been doing full fine-tunes on Mistral using either two A100s (80GB VRAM) with a total batch size of 8, or three A100s (80GB again) with a batch size of 12. This is using the Adam 8-bit optimizer and training with a max sequence length of 4096, lots of long samples. I think it should be possible to do a full fine tune on a single 80GB A100, but I haven't tried. This is without Deep Speed. I've done a few Deep Speed runs and that significantly lowers VRAM usage.
- RunPod is what I've been using and it's straight forward.
- Instilling new knowledge is possible with a fine tune, much less possible with a LoRA. Can't comment on languages. People seem to have had mixed success creating multi-lingual models.
this post was submitted on 23 Nov 2023
1 points (100.0% liked)
LocalLLaMA
1 readers
1 users here now
Community to discuss about Llama, the family of large language models created by Meta AI.
founded 10 months ago
MODERATORS
how much does it cost to do these fine tunes on RunPod? How much compute time is used
Lik $1000+?
you get 14hrs of a100 80gb with 25 dollars.
An A100 ((80GB) costs between $1.70=$1.99 per hour on RunPod. How long you need depends on dataset size, sequence length, the optimizer you choose and how many epochs you train for. I can get a full finetune of Mistral (5 epochs) with an Adam 8-bit optimizer done on my small (1300 samples) but long sequence length (most samples are 4096 tokens) dataset in around an hour with 3x A100s.