BOINC AI Optimum Habana

πŸ€— Optimum Habana

πŸ€— Optimum Habana is the interface between the πŸ€— Transformers and πŸ€— Diffusers libraries and Habana’s Gaudi processor (HPU). It provides a set of tools that enable easy model loading, training and inference on single- and multi-HPU settings for various downstream tasks as shown in the table below.

HPUs offer fast model training and inference as well as a great price-performance ratio. Check out this blog post about BERT pre-training and this article benchmarking Habana Gaudi2 versus Nvidia A100 GPUs for concrete examples. If you are not familiar with HPUs, we recommend you take a look at our conceptual guide.

The following model architectures, tasks and device distributions have been validated for πŸ€— Optimum Habana:

In the tables below, βœ… means single-card, multi-card and DeepSpeed have all been validated.

  • Transformers

Architecture
Training
Inference
Tasks

BLOOM(Z)

❌

  • DeepSpeed

StarCoder

❌

  • Single card

GPT-J

  • DeepSpeed

  • Single card

  • DeepSpeed

GPT-NeoX

  • DeepSpeed

  • DeepSpeed

OPT

❌

  • DeepSpeed

Llama 2 / CodeLlama

  • DeepSpeed

  • LoRA

  • DeepSpeed

  • LoRA

StableLM

❌

  • Single card

Falcon

❌

  • Single card

CodeGen

❌

  • Single card

MPT

❌

  • Single card

ViT

βœ…

βœ…

Swin

βœ…

βœ…

BridgeTower

βœ…

βœ…

ESMFold

❌

  • Single card

  • Diffusers

Architecture
Training
Inference
<center>Tasks</center>

Stable Diffusion

❌

  • Single card

LDM3D

❌

  • Single card

Other models and tasks supported by the 🌍 Transformers and 🌍 Diffusers library may also work. You can refer to this section for using them with 🌍 Optimum Habana. Besides, this page explains how to modify any example from the 🌍 Transformers library to make it work with 🌍 Optimum Habana.

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