I use an M1 as my daily driver, which was given to me by work. I used to be hard line anti-mac, but I have been thoroughly converted. I will say though that mps and PyTorch do not seem to go together very well, and I stick to using the cpu when running models locally.
It's good enough to play around with certain models. For example at the moment I'm currently using BERT and T5-large for inference (on different projects) and they run OK. This is generally the case for inference on small to medium language models. However, for training, fine-tuning, or running bigger language models (or vision models), I work on a remote server with a GPU. Access to a Nvidia GPU, whether locally or remotely, is simply a must have for training or bigger models.
For learning and small models, a macbook and Google colab are very sufficient.
I use an M1 as my daily driver, which was given to me by work. I used to be hard line anti-mac, but I have been thoroughly converted. I will say though that mps and PyTorch do not seem to go together very well, and I stick to using the cpu when running models locally.
It's good enough to play around with certain models. For example at the moment I'm currently using BERT and T5-large for inference (on different projects) and they run OK. This is generally the case for inference on small to medium language models. However, for training, fine-tuning, or running bigger language models (or vision models), I work on a remote server with a GPU. Access to a Nvidia GPU, whether locally or remotely, is simply a must have for training or bigger models.
For learning and small models, a macbook and Google colab are very sufficient.