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--- |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- text-to-image |
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- image-generation |
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- flux |
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base_model: |
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- black-forest-labs/FLUX.1-schnell |
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--- |
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# FLUX.1-schnell-fp16-ov |
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* Model creator: [Black Forset Labs](https://huggingface.co/black-forest-labs) |
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* Original model: [black-forest-labs/FLUX.1-schnell](https://huggingface.co/black-forest-labs/FLUX.1-schnell) |
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## Description |
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This is [black-forest-labs/FLUX.1-schnell](https://huggingface.co/black-forest-labs/FLUX.1-schnell) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/2024/documentation/openvino-ir-format.html) (Intermediate Representation) format. |
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## Compatibility |
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The provided OpenVINO™ IR model is compatible with: |
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* OpenVINO version 2025.0.0 and higher |
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* Optimum Intel 1.23.0 and higher |
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## Running Model Inference with [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) |
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1. Install packages required for using [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) integration with the OpenVINO backend: |
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``` |
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pip install optimum[openvino] |
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``` |
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2. Run model inference: |
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``` |
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from optimum.intel.openvino import OVDiffusionPipeline |
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model_id = "OpenVINO/FLUX.1-schnell-fp16-ov" |
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pipeline = OVDiffusionPipeline.from_pretrained(model_id) |
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prompt = "A cat holding a sign that says hello world" |
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images = pipeline(prompt, guidance_scale=0.0, num_inference_steps=4).images |
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``` |
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## Running Model Inference with [OpenVINO GenAI](https://github.com/openvinotoolkit/openvino.genai) |
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1. Install packages required for using OpenVINO GenAI. |
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``` |
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pip install huggingface_hub |
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pip install -U --pre --extra-index-url https://storage.openvinotoolkit.org/simple/wheels/nightly openvino openvino-tokenizers openvino-genai |
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``` |
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2. Download model from HuggingFace Hub |
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``` |
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import huggingface_hub as hf_hub |
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model_id = "OpenVINO/FLUX.1-schnell-fp16-ov" |
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model_path = "FLUX.1-schnell-fp16-ov" |
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hf_hub.snapshot_download(model_id, local_dir=model_path) |
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``` |
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3. Run model inference: |
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``` |
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import openvino_genai as ov_genai |
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from PIL import Image |
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device = "CPU" |
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pipe = ov_genai.Text2ImagePipeline(model_path, device, guidance_scale=0.0, num_inference_steps=4) |
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prompt = "A cat holding a sign that says hello world" |
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image_tensor = pipe.generate(prompt) |
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image = Image.fromarray(image_tensor.data[0]) |
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``` |
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More GenAI usage examples can be found in OpenVINO GenAI library [docs](https://github.com/openvinotoolkit/openvino.genai/blob/master/src/README.md) and [samples](https://github.com/openvinotoolkit/openvino.genai?tab=readme-ov-file#openvino-genai-samples) |
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## Limitations |
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Check the original [model card](https://huggingface.co/black-forest-labs/FLUX.1-schnell) for limitations. |
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## Legal information |
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The original model is distributed under [Apache 2.0](https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/apache-2.0.md) license. More details can be found in [model card](https://huggingface.co/black-forest-labs/FLUX.1-schnell). |
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## Disclaimer |
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Intel is committed to respecting human rights and avoiding causing or contributing to adverse impacts on human rights. See [Intel’s Global Human Rights Principles](https://www.intel.com/content/dam/www/central-libraries/us/en/documents/policy-human-rights.pdf). Intel’s products and software are intended only to be used in applications that do not cause or contribute to adverse impacts on human rights. |
