Suggest a model to fine-tune for multi-class classification on a 32GB M1 Mac?
Can anyone suggest a model I could use to experiment with fine-tuning for multi-class classification on a 32GB RAM M1 Max MacBook Pro? I’m using the Huggingface Transformers library with the mps device so it runs on the Mac’s GPU.I’ve triedbert-base-cased, but its token window is only 512, which isn’t enough for my use case—I need 2k-4k. I’ve triedMixtral-8x7B-v0.1, but it hangs halfway through the training run. I just triedlongformer-base-4096but it runs out of memory.Can someone suggest something that has a chance of working?Edit: if it matters, there area lotof classes—around 160.
2024-03-04T13:51:16Z
If your usecase is related to multi-class classification then I think you should try setfit. Hugging Face have a very good starter blog for thishuggingface.coSetFit: Efficient Few-Shot Learning Without PromptsWe’re on a journey to advance and democratize artificial intelligence through open source and open science.you can go withsentence-transformers/paraphrase-mpnet-base-v2this model