Topic

Diffusers

1 post about Diffusers. Every summary links to the original.

Paid picks we use ourselves. Links carry a referral code — a subscription through one earns us a commission at no extra cost to you.

Newest first

Posts

Hugging Face
Hugging Face ❤️ TorchTPU: TPUs, Natively
TorchTPU adds a native PyTorch backend for Google TPUs, eliminating the need for torch_xla or JAX. Installing it on a TPU VM requires a single pip command with a CPU-only torch index. Users can load any Hugging Face model onto a TPU with device_map=“tpu” and run it in eager mode without code changes. Diffusers pipelines also support TPU natively, requiring only pipe.to(“tpu”) for eager execution or an optional compile call for deployment. The Kernels Hub provides ready-to-use TPU kernels written in Pallas, which can accelerate MoE models by over 20× at large batch sizes, as demonstrated with Qwen3-30B-A3B. The Hugging Face team is continuously testing TPU support, with 96.5% of tests passing and upstream fixes for discovered issues, including bugs in StaticCache and Qwen3 tensor-parallel plans.

The best engineering reads, once a week.

Topic

1 post about Diffusers. Every summary links to the original.

Paid picks we use ourselves. Links carry a referral code — a subscription through one earns us a commission at no extra cost to you.

Newest first

Hugging Face
Hugging Face ❤️ TorchTPU: TPUs, Natively
TorchTPU adds a native PyTorch backend for Google TPUs, eliminating the need for torch_xla or JAX. Installing it on a TPU VM requires a single pip command with a CPU-only torch index. Users can load any Hugging Face model onto a TPU with device_map=“tpu” and run it in eager mode without code changes. Diffusers pipelines also support TPU natively, requiring only pipe.to(“tpu”) for eager execution or an optional compile call for deployment. The Kernels Hub provides ready-to-use TPU kernels written in Pallas, which can accelerate MoE models by over 20× at large batch sizes, as demonstrated with Qwen3-30B-A3B. The Hugging Face team is continuously testing TPU support, with 96.5% of tests passing and upstream fixes for discovered issues, including bugs in StaticCache and Qwen3 tensor-parallel plans.

The best engineering reads, once a week.