Add pipeline tag, library name, and sample usage

This PR improves the model card for Cosmos3-Super by:
- Adding the `pipeline_tag: any-to-any` to reflect its omnimodal capabilities.
- Setting `library_name: diffusers` to enable the Hub's automated code snippets.
- Adding a sample usage section with a code snippet for the `diffusers` integration.
- Including a link to the paper page on Hugging Face.

README.md

@@ -1,22 +1,22 @@
 ---
+library_name: diffusers
 license: other
 license_name: openmdw1.1-license
-license_link: >-
-  https://openmdw.ai/license/1-1/
-library_name: cosmos
+license_link: https://openmdw.ai/license/1-1/
+pipeline_tag: any-to-any
 tags:
-  - nvidia
-  - cosmos
-  - cosmos3
-  - vllm
-  - vllm-omni
-  - diffusers
-  - text, image, video, audio, and action generation
-  - omnimodel
+- nvidia
+- cosmos
+- cosmos3
+- vllm
+- vllm-omni
+- diffusers
+- text, image, video, audio, and action generation
+- omnimodel
 ---
 
 # **Cosmos 3: Omnimodal World Models for Physical AI**
-**[Model Collection](https://huggingface.co/collections/nvidia/cosmos3)** | **[Code](https://github.com/nvidia/cosmos)** | **[White Paper](https://research.nvidia.com/labs/cosmos-lab/cosmos3/technical-report.pdf)** | **[Website](https://research.nvidia.com/labs/cosmos-lab/cosmos3/)**
+**[Paper Page](https://huggingface.co/papers/2606.02800)** | **[Model Collection](https://huggingface.co/collections/nvidia/cosmos3)** | **[Code](https://github.com/nvidia/cosmos)** | **[White Paper](https://research.nvidia.com/labs/cosmos-lab/cosmos3/technical-report.pdf)** | **[Website](https://research.nvidia.com/labs/cosmos-lab/cosmos3/)**
 
 [NVIDIA Cosmos™](https://github.com/nvidia/cosmos) is a world foundation model platform designed to accelerate the development of Physical AI by enabling machines to understand, simulate, and interact with the physical world across robotics, autonomous driving, and smart space environments, including industrial and factory-scale applications.
 
@@ -30,6 +30,37 @@ This model is ready for commercial and non-commercial use.
 
 **Model Developer:** NVIDIA
 
+### Sample Usage
+
+You can use the model with the [diffusers](https://github.com/huggingface/diffusers) library as shown below:
+
+```python
+import torch
+from diffusers import Cosmos3OmniPipeline
+from diffusers.schedulers.scheduling_unipc_multistep import UniPCMultistepScheduler
+from diffusers.utils import export_to_video
+
+pipe = Cosmos3OmniPipeline.from_pretrained(
+    "nvidia/Cosmos3-Super",
+    torch_dtype=torch.bfloat16,
+    device_map="cuda",
+)
+pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config, flow_shift=10.0)
+
+result = pipe(
+    prompt="A mobile robot navigates a warehouse aisle and stops at a shelf.",
+    num_frames=189,
+    height=720,
+    width=1280,
+    fps=24,
+    num_inference_steps=35,
+    guidance_scale=6.0,
+    generator=torch.Generator(device="cuda").manual_seed(123),
+)
+
+export_to_video(result.video, "cosmos3_super_t2v.mp4", fps=24)
+```
+
 ### Model Versions
 - Cosmos3-Nano:
   - Given multimodal inputs including text, images, video, audio, and action trajectories, generate coherent text, images, video, audio, and action outputs for multimodal understanding, world simulation, future prediction, action reasoning, and Physical AI applications.
@@ -816,7 +847,7 @@ client = openai.OpenAI(
     base_url="http://localhost:8000/v1",
 )
 
-response = client.chat.completions.create(
+response = client.chat.completion.create(
     model=client.models.list().data[0].id,
     messages=[
         {
@@ -941,4 +972,4 @@ Please make sure you have proper rights and permissions for all input image and
 
 Users are responsible for model inputs and outputs. Users are responsible for ensuring safe integration of this model, including implementing guardrails as well as other safety mechanisms, prior to deployment.
 
-For more detailed information on ethical considerations for this model, please see the Model Card++ [Explainability](EXPLAINABILITY.md), [Bias](BIAS.md), [Safety & Security](SAFETY.md), and [Privacy](PRIVACY.md) subcards. Please report model quality, risk, security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).
+For more detailed information on ethical considerations for this model, please see the Model Card++ [Explainability](EXPLAINABILITY.md), [Bias](BIAS.md), [Safety & Security](SAFETY.md), and [Privacy](PRIVACY.md) subcards. Please report model quality, risk, security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).