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docs/source_en/GetStarted/A_simple_example.md

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+# A Simple Example: Text-to-Image Synthesis with Flux
+
+The following example shows how to use the FLUX.1 model for text-to-image tasks. The script provides a simple setup for generating images from text descriptions. It covers downloading the necessary models, configuring the pipeline, and generating images with and without classifier-free guidance.
+
+For other models supported by DiffSynth, see [Models.md](Models.md).
+
+## Setup
+
+First, ensure you have the necessary models downloaded and configured:
+
+```python
+import torch
+from diffsynth import ModelManager, FluxImagePipeline, download_models
+
+# Download the FLUX.1-dev model files
+download_models(["FLUX.1-dev"])
+```
+
+For instructions on downloading models, see [Download_models.md](Download_models.md).
+
+## Loading Models
+Initialize the model manager with your device and data type:
+
+```python
+model_manager = ModelManager(torch_dtype=torch.bfloat16, device="cuda")
+model_manager.load_models([
+    "models/FLUX/FLUX.1-dev/text_encoder/model.safetensors",
+    "models/FLUX/FLUX.1-dev/text_encoder_2",
+    "models/FLUX/FLUX.1-dev/ae.safetensors",
+    "models/FLUX/FLUX.1-dev/flux1-dev.safetensors"
+])
+```
+
+For instructions on loading models, see [ModelManager.md](ModelManager.md).
+
+## Creating the Pipeline
+Create an instance of the FluxImagePipeline from the loaded model manager:
+
+
+```python
+pipe = FluxImagePipeline.from_model_manager(model_manager)
+```
+
+For instructions on using the Pipeline, see [Pipeline.md](Pipeline.md).
+## Text-to-Image Synthesis
+Generate an image using a short prompt. Below are examples of generating images with and without classifier-free guidance.
+
+### Basic Generation
+```python
+prompt = "A cute little turtle"
+negative_prompt = ""
+
+torch.manual_seed(6)
+image = pipe(
+    prompt=prompt,
+    num_inference_steps=30, embedded_guidance=3.5
+)
+image.save("image_1024.jpg")
+```
+
+### Generation with Classifier-Free Guidance
+```python
+torch.manual_seed(6)
+image = pipe(
+    prompt=prompt, negative_prompt=negative_prompt,
+    num_inference_steps=30, cfg_scale=2.0, embedded_guidance=3.5
+)
+image.save("image_1024_cfg.jpg")
+```
+
+### High-Resolution Fix
+```python
+torch.manual_seed(7)
+image = pipe(
+    prompt=prompt,
+    num_inference_steps=30, embedded_guidance=3.5,
+    input_image=image.resize((2048, 2048)), height=2048, width=2048, denoising_strength=0.6, tiled=True
+)
+image.save("image_2048_highres.jpg")
+```
+