Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

Optimum RBLN

Optimum RBLN

PyPI version License Documentation Contributor Covenant

🤗 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

Swap the HuggingFace class for its RBLN counterpart. Passing a HuggingFace model id compiles the model for the NPU on the first run; passing a directory of previously compiled artifacts loads them directly, so compilation is skipped.

- 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)

# 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")

Compile Ahead of Time with the CLI

Instead of compiling inside your script, you can compile a model up front with the optimum-rbln-cli command and load the resulting artifacts later:

# Compile and save the artifacts to ./compiled_qwen3
optimum-rbln-cli --model-id Qwen/Qwen3-4B -o ./compiled_qwen3 \
    --max_seq_len 8192 --batch_size 1 --num_devices 4
from optimum.rbln import RBLNQwen3ForCausalLM

# Load the compiled artifacts (no recompilation)
model = RBLNQwen3ForCausalLM.from_pretrained("./compiled_qwen3")

Useful CLI helpers:

optimum-rbln-cli --list-classes                     # list available RBLN classes
optimum-rbln-cli --class RBLNQwen3ForCausalLM --show-rbln-config  # show accepted rbln_config keys
optimum-rbln-cli --examples                          # show more usage examples

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 --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?

Metadata

Release files for optimum-rbln 0.12.1a0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for optimum-rbln 0.12.1a0
File Size Uploaded
optimum_rbln-0.12.1a0.tar.gz 679.6 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for optimum-rbln 0.12.1a0
File Interpreter ABI Platform
optimum_rbln-0.12.1a0-py3-none-any.whl Python 3 none any Details

Total release size: 1.4 MB

Release files / optimum_rbln-0.12.1a0.tar.gz

Download URL optimum_rbln-0.12.1a0.tar.gz
Size 679.6 kB
Tags Source
SHA-256 checksum
How to use checksums
1f78f5d496430124c21676364d86389dcd07469eba82156de36b4fc1acf47940
BLAKE2b-256 checksum
How to use checksums
5468e405ac4656e7c231681bd1e93fc21ce0bbb0a75c39b9cd157be9602556c4
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.3

Release files / optimum_rbln-0.12.1a0-py3-none-any.whl

Download URL optimum_rbln-0.12.1a0-py3-none-any.whl
Size 721.0 kB
Tags Python 3
SHA-256 checksum
How to use checksums
ed70f5dcae2caf6b2cc74c85c9136bc682ce53db0989dcb5c43dc68dd2ca32f9
BLAKE2b-256 checksum
How to use checksums
0b21f36fa9018309907d74a7ebb45249478343a47368db8a1b1fe6f81e9b6498
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.3

Release history Release notifications | RSS feed

This release

0.12.1a0 This release

2 release files

0.12.0

2 release files

0.11.2

2 release files

0.11.1

2 release files

0.10.4

2 release files

0.10.3

2 release files

0.10.2

2 release files

0.10.1

2 release files

0.10.0

2 release files

0.9.4

2 release files

0.9.3

2 release files

0.9.2

2 release files

0.9.1

2 release files

0.8.3

2 release files

0.8.2

2 release files

0.8.1

2 release files

0.8.0

2 release files

0.7.4

2 release files

0.7.2

2 release files

0.2.0

1 release file

0.1.15

1 release file

0.1.13

1 release file

0.1.12

1 release file

0.1.11

1 release file

0.1.9

1 release file

0.1.8

1 release file

0.1.7

1 release file

0.1.4

1 release file

0.1.1

1 release file

0.1.0

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page