onnx-fix
#27
by
echarlaix
HF staff
- opened
- README.md +9 -9
- model_index.json +0 -1
- sd_xl_base_1.0_0.9vae.safetensors +0 -3
- text_encoder/flax_model.msgpack +0 -3
- text_encoder/openvino_model.bin +0 -3
- text_encoder/openvino_model.xml +0 -3
- text_encoder_2/flax_model.msgpack +0 -3
- text_encoder_2/openvino_model.bin +0 -3
- text_encoder_2/openvino_model.xml +0 -3
- unet/diffusion_flax_model.msgpack +0 -3
- unet/openvino_model.bin +0 -3
- unet/openvino_model.xml +0 -3
- vae/config.json +1 -2
- vae/diffusion_flax_model.msgpack +0 -3
- vae/diffusion_pytorch_model.fp16.safetensors +1 -1
- vae/diffusion_pytorch_model.safetensors +1 -1
- vae_1_0/config.json +0 -31
- vae_1_0/diffusion_pytorch_model.fp16.safetensors +0 -3
- vae_1_0/diffusion_pytorch_model.safetensors +0 -3
- vae_decoder/config.json +2 -1
- vae_decoder/openvino_model.bin +0 -3
- vae_decoder/openvino_model.xml +0 -3
- vae_encoder/config.json +2 -1
- vae_encoder/openvino_model.bin +0 -3
- vae_encoder/openvino_model.xml +0 -3
README.md
CHANGED
@@ -33,7 +33,7 @@ Source code is available at https://github.com/Stability-AI/generative-models .
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### Model Sources
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-
For research purposes, we
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[Clipdrop](https://clipdrop.co/stable-diffusion) provides free SDXL inference.
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- **Repository:** https://github.com/Stability-AI/generative-models
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@@ -146,12 +146,12 @@ pip install optimum[openvino]
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To load an OpenVINO model and run inference with OpenVINO Runtime, you need to replace `StableDiffusionXLPipeline` with Optimum `OVStableDiffusionXLPipeline`. In case you want to load a PyTorch model and convert it to the OpenVINO format on-the-fly, you can set `export=True`.
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```diff
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-
- from diffusers import
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-
+ from optimum.intel import
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model_id = "stabilityai/stable-diffusion-xl-base-1.0"
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-
- pipeline =
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+ pipeline =
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prompt = "A majestic lion jumping from a big stone at night"
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image = pipeline(prompt).images[0]
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```
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@@ -170,12 +170,12 @@ pip install optimum[onnxruntime]
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To load an ONNX model and run inference with ONNX Runtime, you need to replace `StableDiffusionXLPipeline` with Optimum `ORTStableDiffusionXLPipeline`. In case you want to load a PyTorch model and convert it to the ONNX format on-the-fly, you can set `export=True`.
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```diff
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-
- from diffusers import
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+ from optimum.onnxruntime import
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model_id = "stabilityai/stable-diffusion-xl-base-1.0"
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-
- pipeline =
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+ pipeline =
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prompt = "A majestic lion jumping from a big stone at night"
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image = pipeline(prompt).images[0]
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```
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### Model Sources
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+
For research purposes, we recommned our `generative-models` Github repository (https://github.com/Stability-AI/generative-models), which implements the most popoular diffusion frameworks (both training and inference) and for which new functionalities like distillation will be added over time.
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[Clipdrop](https://clipdrop.co/stable-diffusion) provides free SDXL inference.
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- **Repository:** https://github.com/Stability-AI/generative-models
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To load an OpenVINO model and run inference with OpenVINO Runtime, you need to replace `StableDiffusionXLPipeline` with Optimum `OVStableDiffusionXLPipeline`. In case you want to load a PyTorch model and convert it to the OpenVINO format on-the-fly, you can set `export=True`.
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```diff
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- from diffusers import StableDiffusionPipeline
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+ from optimum.intel import OVStableDiffusionPipeline
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model_id = "stabilityai/stable-diffusion-xl-base-1.0"
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+
- pipeline = StableDiffusionPipeline.from_pretrained(model_id)
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+ pipeline = OVStableDiffusionPipeline.from_pretrained(model_id)
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prompt = "A majestic lion jumping from a big stone at night"
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image = pipeline(prompt).images[0]
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```
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To load an ONNX model and run inference with ONNX Runtime, you need to replace `StableDiffusionXLPipeline` with Optimum `ORTStableDiffusionXLPipeline`. In case you want to load a PyTorch model and convert it to the ONNX format on-the-fly, you can set `export=True`.
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```diff
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- from diffusers import StableDiffusionPipeline
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+ from optimum.onnxruntime import ORTStableDiffusionPipeline
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model_id = "stabilityai/stable-diffusion-xl-base-1.0"
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+
- pipeline = StableDiffusionPipeline.from_pretrained(model_id)
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+ pipeline = ORTStableDiffusionPipeline.from_pretrained(model_id)
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prompt = "A majestic lion jumping from a big stone at night"
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image = pipeline(prompt).images[0]
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```
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model_index.json
CHANGED
@@ -2,7 +2,6 @@
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"_class_name": "StableDiffusionXLPipeline",
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"_diffusers_version": "0.19.0.dev0",
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"force_zeros_for_empty_prompt": true,
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-
"add_watermarker": null,
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"scheduler": [
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"diffusers",
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"EulerDiscreteScheduler"
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"_class_name": "StableDiffusionXLPipeline",
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"_diffusers_version": "0.19.0.dev0",
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"force_zeros_for_empty_prompt": true,
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"scheduler": [
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"diffusers",
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"EulerDiscreteScheduler"
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sd_xl_base_1.0_0.9vae.safetensors
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vae/config.json
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vae_1_0/config.json
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vae_decoder/config.json
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vae_decoder/openvino_model.xml
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vae_encoder/config.json
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