optimum-rbln 0.10.0.post2

Optimum RBLN is the interface between the HuggingFace Transformers and Diffusers libraries and RBLN accelerators. It provides a set of tools enabling easy model loading and inference on single and multiple rbln device settings for different downstream tasks.

Optimum RBLN

🤗 Optimum RBLN provides an interface between HuggingFace libraries (Transformers, Diffusers) and RBLN NPUs, including ATOM and REBEL.

This library enables seamless integration between the HuggingFace ecosystem and RBLN NPUs through a comprehensive toolkit for model loading and inference across single and multi-NPU environments. While we maintain a list of officially validated models and tasks, users can easily adapt other models and tasks with minimal modifications.

Key Features

🚀 High Performance Inference

• Optimized model execution on RBLN NPUs through RBLN SDK compilation
• Support for both single and multi-NPU inference
• Integrated with RBLN Runtime for optimal performance

🔧 Easy Integration

• Seamless compatibility with HuggingFace Model Hub
• Drop-in replacement for existing HuggingFace pipelines
• Minimal code changes required for NPU acceleration

Seamless Replacement for Existing HuggingFace Code

- from diffusers import StableDiffusionXLPipeline
+ from optimum.rbln import RBLNStableDiffusionXLPipeline

# Load model
model_id = "stabilityai/stable-diffusion-xl-base-1.0"
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
- pipe = StableDiffusionXLPipeline.from_pretrained(model_id)
+ pipe = RBLNStableDiffusionXLPipeline.from_pretrained(model_id, export=True)

# Generate image
image = pipe(prompt).images[0]

# Save image result
image.save("image.png")

+ # (Optional) Save compiled artifacts to skip the compilation step in future runs
+ pipe.save_pretrained("compiled_sdxl")

Documentation

Check out the documentation of Optimum RBLN for more advanced usage.

Getting Started

Note: The rebel-compiler library, which is required for running optimum-rbln, is only available for approved users. Please refer to the installation guide for instructions on accessing and installing rebel-compiler.

Install from PyPI

To install the latest release of this package:

pip install optimum-rbln

# CPU-only installation (recommended if you don't plan to use CUDA-enabled PyTorch)
pip install optimum-rbln --extra-index-url https://download.pytorch.org/whl/cpu

Install from source

Prerequisites

• Install uv (refer to this link for detailed commands)

The below command installs optimum-rbln along with its dependencies.

git clone https://github.com/rbln-sw/optimum-rbln.git
cd optimum-rbln
./scripts/uv-sync.sh

Need Help?

• Join discussions and get answers in our Developer Community
• Contact maintainers at [e-mail]