AI BriefingGraphcore Releases Transformers for IPU
Key point
A variety of Transformer models optimized for Graphcore IPUs have been added to the Hugging Face Optimum library.
Details
Graphcore and Hugging Face have unveiled a new lineup of Transformer models that deliver optimal performance on Graphcore's IPU (Intelligence Processing Unit) through the Hugging Face Optimum library.
With this update, developers can now immediately use 10 models spanning NLP, speech, and computer vision. Each model includes IPU-specific configuration files along with pre-trained and fine-tuned weights.
Key models by field:
- Computer Vision: ViT (Vision Transformer)
- NLP: GPT-2, RoBERTa, DeBERTa, BART, LXMERT, T5
- Speech: HuBERT
These models are optimized to deliver efficient performance in IPU environments, making them immediately applicable to a variety of multimodal and language processing tasks.
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