update org card (#3)

- update org card (8c5f1a21a68014cfced04876bdcd3ed04eead000)
- Update README.md (97d2cf7fc5d8118c01f4ad6a8d834e1b80931bde)


Co-authored-by: Steven Liu <[email protected]>

README.md

@@ -7,10 +7,30 @@ sdk: static
 pinned: false
 ---
 
-# Welcome to the 🧨 `diffusers` organization!
+<div class="flex justify-center">
+    <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/diffusers-org-logo.png"/>
+</div>
 
-`diffusers` is the go-to library for state-of-the-art pretrained diffusion models for multi-modal generative AI.
+[Diffusers](https://github.com/huggingface/diffusers) is a library of state-of-the-art pretrained diffusion models for *all* of your generative AI needs and use cases.
 
-[GitHub](https://github.com/huggingface/diffusers), [Docs](https://huggingface.co/docs/diffusers/index)
+The library provides three main classes.
 
-In this organization, you can find some utilities and models we have made for you 🫶
+1. The [Pipeline](https://hf.co/docs/diffusers/api/pipelines/overview) class provides an easy and unified way to perform inference with many models.
+
+```py
+import torch
+from diffusers import FluxPipeline
+
+pipeline = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16)
+pipeline.enable_model_cpu_offload()
+
+prompt = "A cat holding a sign that says hello world"
+image = pipeline(prompt, guidance_scale=0.0, output_type="pil", num_inference_steps=4, max_sequence_length=256, generator=torch.Generator("cpu").manual_seed(33)).images[0]
+image.save("flux-schnell.png")
+```
+
+2. Diffusers also provides [models](https://hf.co/docs/diffusers/api/models/overview) and [schedulers](https://hf.co/docs/diffusers/api/schedulers/overview) that you can mix and match to build or train your own diffusion systems.
+
+In addition to these classes, Diffusers is invested in lowering the barrier for everyone. The library is optimized to run on memory-constrained hardware, accelerate inference on PyTorch, hardware (GPU/CPU/TPUs), and model accelerators.
+
+Visit the [documentation](https://hf.co/docs/diffusers/index) if you're interested in learning more. We're excited to see what you create with Diffusers! 🤗