50ec9702d0
Co-authored-by: Mick Qian <mickqian@users.noreply.github.com> Co-authored-by: Claude Opus 5 <noreply@anthropic.com>
90 lines
3.1 KiB
Plaintext
90 lines
3.1 KiB
Plaintext
---
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title: ERNIE-Image
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metatags:
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description: "Deploy ERNIE-Image and ERNIE-Image-Turbo with SGLang Diffusion."
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---
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import { DiffusionModelTags } from '/src/snippets/diffusion/model-tags.jsx';
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<DiffusionModelTags tags={["image", "text-to-image", "standard + Turbo", "single GPU"]} />
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## 1. Model Introduction
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[ERNIE-Image](https://huggingface.co/baidu/ERNIE-Image) is Baidu's text-to-image family with separate standard and Turbo checkpoints. The standard model is the quality-oriented path; Turbo is the lower-latency choice, and both load through SGLang's native `ErnieImagePipeline`.
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This integration currently targets text-only image generation rather than image editing or reference conditioning. Choose it for a straightforward single-GPU T2I deployment; use a dedicated editing model when preserving source-image structure is part of the task.
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| Model | Hugging Face model ID | Notes |
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| --- | --- | --- |
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| ERNIE-Image | `baidu/ERNIE-Image` | Regular text-to-image checkpoint |
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| ERNIE-Image-Turbo | `baidu/ERNIE-Image-Turbo` | Turbo text-to-image checkpoint |
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## 2. Installation
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Install SGLang with the diffusion dependencies:
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```bash Command
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pip install -e "python[diffusion]"
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```
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For full installation options, see the [SGLang Diffusion installation guide](/docs/sglang-diffusion/installation).
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## 3. Serve the model
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The commands below target a single supported NVIDIA CUDA or AMD ROCm GPU. Start with `--performance-mode auto`; use `speed` only when the full pipeline fits comfortably on the selected GPU(s), and use `memory` when you need lower peak GPU memory.
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Serve ERNIE-Image:
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```bash Command
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sglang serve \
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--model-path baidu/ERNIE-Image \
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--num-gpus 1 \
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--performance-mode auto \
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--port 30010
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```
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Serve ERNIE-Image-Turbo:
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```bash Command
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sglang serve \
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--model-path baidu/ERNIE-Image-Turbo \
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--num-gpus 1 \
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--performance-mode auto \
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--port 30010
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```
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## 4. Generate an image
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Use the OpenAI-compatible image generation API after the server starts:
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```python Python
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import base64
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from openai import OpenAI
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client = OpenAI(api_key="EMPTY", base_url="http://127.0.0.1:30010/v1")
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response = client.images.generate(
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model="baidu/ERNIE-Image-Turbo",
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prompt="A cinematic photo of a quiet lakeside cabin at sunrise",
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n=1,
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response_format="b64_json",
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)
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image_bytes = base64.b64decode(response.data[0].b64_json)
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with open("ernie_image.png", "wb") as f:
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f.write(image_bytes)
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```
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## 5. Configuration tips
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- ERNIE-Image is a text-to-image pipeline; do not pass `--image-path`.
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- `--performance-mode auto` keeps conservative defaults while preserving explicit user flags.
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- If the checkpoint includes a PE component, SGLang loads it automatically with the native Ministral3 runtime. Use `--layerwise-offload-components pe` when the local PE decoder needs to trade latency for lower GPU memory usage.
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- Treat FSDP, SP/Ulysses/Ring, and TP as explicit benchmark knobs. Measure the target resolution, step count, and GPU type before making them production defaults.
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## 6. Run in ComfyUI
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import { ComfyUISupport } from '/src/snippets/diffusion/comfyui-support.jsx';
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<ComfyUISupport model="image" />
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