baidu
/

ERNIE-Image

@@ -4,195 +4,115 @@ license: apache-2.0
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 # Model Card for Model ID
 ## Model Details
 ### Model Description
+1. Overview
+**ERNIE-Image** is a text-to-image generation model developed by the ERNIE team at Baidu.
+In terms of image quality, ERNIE-Image is on par with current state-of-the-art models. It demonstrates significant advantages in handling complex instructions, particularly in tasks that require **accurate text rendering** and **knowledge-intensive generation**.
+### Key Features
+* **Precise text rendering**: Especially strong in dense or complex text scenarios
+* **Excellent instruction following**: Accurately interprets and executes complex prompts
+* **High-quality portraits and stylized images**: Strong performance in both realism and artistic styles
+### Model Architecture
+ERNIE-Image consists of the following components:
+* An 8B-parameter Diffusion Transformer (DiT)
+* A 3B text encoder from Ministral
+* A VAE based on flux2.dev
+* A prompt enhancer fine-tuned using Ministral 3B
+### Deployment
+Thanks to its relatively compact model size, ERNIE-Image can be deployed on **consumer-grade GPUs (e.g., 24GB VRAM)**, making high-quality image generation more accessible and practical.
 ## Evaluation
+### Benchmark
+### Showcase
+## Uses
+### Installation & Download
+Install the latest version of diffusers:
+```
+pip install git+https://github.com/huggingface/diffusers
+```
+Download the model:
+```
+pip install -U huggingface_hub
+HF_XET_HIGH_PERFORMANCE=1 hf download baidu/ERNIE-Image
+### Recommended Parameters
+- Resolution:
+    - 1024x1024
+    - 848x1264
+    - 1264x848
+    - 768x1376
+    - 896x1200
+    - 1376x768
+    - 1200x896
+- Guidance scale: 4.0
+- Inference steps: 50
+```
+### Usage Example
+```
+import os
+os.environ["CUBLAS_WORKSPACE_CONFIG"] = ":4096:8"
+import random
+import numpy as np
+import torch
+from diffusers import ErnieImagePipeline
+seed = 42
+print(f"seed: {seed}")
+random.seed(seed)
+np.random.seed(seed)
+torch.manual_seed(seed)
+torch.cuda.manual_seed_all(seed)
+torch.backends.cudnn.deterministic = True
+torch.use_deterministic_algorithms(True)
+torch.backends.cudnn.benchmark = False
+# 加载 pipeline
+pipe = ErnieImagePipeline.from_pretrained(
+    "baidu/ERNIE-Image",
+    torch_dtype=torch.bfloat16,
+)
+pipe = pipe.to("cuda")
+pipe.transformer.eval()
+pipe.vae.eval()
+pipe.text_encoder.eval()
+pipe.pe.eval()
+# 如果是消费级显卡,例如 Nvidia 3090
+# pipe.enable_model_cpu_offload()
+# 设置随机种子
+generator = torch.Generator(device="cuda").manual_seed(seed)
+# 生成图片
+output = pipe(
+    prompt=prompt,
+    height=1024,
+    width=1024,
+    num_inference_steps=50,
+    guidance_scale=5.0,
+    generator=generator,
+    num_images_per_prompt=1,
+    use_pe=True
+)
+revised_prompt = output.revised_prompts
+images = output.images
+image.save(f"./hf_output_0.png")
+print(revised_prompt)
+```