Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+base_model:
+- Wan-AI/Wan2.2-T2V-A14B-Diffusers
+base_model_relation: quantized
+pipeline_tag: text-to-video
+---
+
+
+# Elastic model: Fastest self-serving models. Wan 2.2
+
+Elastic models are the models produced by TheStage AI ANNA: Automated Neural Networks Accelerator. ANNA allows you to control model size, latency and quality with a simple slider movement. For each model, ANNA produces a series of optimized models:
+
+* __S__: The fastest model, with accuracy degradation less than 2%.
+
+
+__Goals of Elastic Models:__
+
+* Provide the fastest models and service for self-hosting.
+* Provide flexibility in cost vs quality selection for inference.
+* Provide clear quality and latency benchmarks.
+* Provide interface of HF libraries: transformers and diffusers with a single line of code.
+* Provide models supported on a wide range of hardware, which are pre-compiled and require no JIT.
+
+> It's important to note that specific quality degradation can vary from model to model. For instance, with an S model, you can have 0.5% degradation as well.
+
+-----
+Prompt: Massive ocean waves violently crashing and shattering against jagged rocky cliffs during an intense storm with lightning flashes
+
+Resolution: 480x480, Number of frames: 81
+
+| S | Original |
+|:-:|:-:|
+| https://cdn-uploads.huggingface.co/production/uploads/6799fc8e150f5a4014b030ca/fFhpSm1JdZNxnoSmr6tZ0.mp4 | https://cdn-uploads.huggingface.co/production/uploads/6799fc8e150f5a4014b030ca/ctx01OzYgKDBd-N6xsE4E.mp4|
+
+## Inference
+
+> Compiled versions are currently available only for 81-frame generations at 480x480 resolution. Other versions are not yet accessible. Stay tuned for updates!
+
+To infer our models, you just need to replace `diffusers` import with `elastic_models.diffusers`:
+
+
+```python
+import torch
+from elastic_models.diffusers import WanPipeline
+from diffusers.utils import export_to_video
+
+model_name = "Wan-AI/Wan2.2-T2V-A14B-Diffusers"
+device = torch.device("cuda")
+dtype = torch.bfloat16
+
+pipe = WanPipeline.from_pretrained(
+    model_name,
+    torch_dtype=dtype,
+    mode="S"
+)
+pipe.vae.enable_tiling()
+pipe.vae.enable_slicing()
+pipe.to(device)
+
+prompt = "A beautiful woman in a red dress dancing"
+
+with torch.no_grad():
+    output = pipe(
+        prompt=prompt,
+        negative_prompt="",
+        height=480,
+        width=480,
+        num_frames=81,
+        num_inference_steps=40,
+        guidance_scale=3.0,
+        guidance_scale_2=2.0,
+        generator=torch.Generator("cuda").manual_seed(42),
+    )
+
+    video = output.frames[0]
+    export_to_video(video, "wan_output.mp4", fps=16)
+```
+
+### Installation
+
+
+__System requirements:__
+* GPUs: H100
+* CPU: AMD, Intel
+* Python: 3.10-3.12
+
+
+To work with our models just run these lines in your terminal:
+
+```shell
+pip install thestage
+pip install 'thestage-elastic-models[nvidia]' --extra-index-url https://thestage.jfrog.io/artifactory/api/pypi/pypi-thestage-ai-production/simple
+
+pip install flash_attn==2.7.3 --no-build-isolation
+pip uninstall apex
+pip install tensorrt==10.11.0.33 opencv-python==4.11.0.86 imageio-ffmpeg==0.6.0
+```
+
+Then go to [app.thestage.ai](https://app.thestage.ai), login and generate API token from your profile page. Set up API token as follows:
+
+```shell
+thestage config set --api-token <YOUR_API_TOKEN>
+```
+
+Congrats, now you can use accelerated models!
+
+----
+
+## Benchmarks
+
+Benchmarking is one of the most important procedures during model acceleration. We aim to provide clear performance metrics for models using our algorithms.
+
+
+### Latency benchmarks
+
+Time in seconds of generation for 480x480 resolution, 81 frames.
+
+
+| GPU  | S   | Original |
+|----------|-----|----------|
+| H100     | 90  | 180      |
+
+
+## Links
+
+* __Platform__: [app.thestage.ai](https://app.thestage.ai)
+<!-- * __Elastic models Github__: [app.thestage.ai](app.thestage.ai) -->
+* __Subscribe for updates__: [TheStageAI X](https://x.com/TheStageAI)
+* __Contact email__: contact@thestage.ai