Update README.md

README.md

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 license: mit
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+
+[`SimianLuo/LCM_Dreamshaper_v7`](https://huggingface.co/SimianLuo/LCM_Dreamshaper_v7) compiled on an AWS Inf2 instance. ***INF2/TRN1 ONLY***
+
+***How to use***
+
+```python
+from optimum.neuron import NeuronLatentConsistencyModelPipeline
+
+pipe = NeuronLatentConsistencyModelPipeline.from_pretrained("Jingya/LCM_Dreamshaper_v7_neuronx")
+
+num_images_per_prompt = 2
+prompt = ["Self-portrait oil painting, a beautiful cyborg with golden hair, 8k"] * num_images_per_prompt
+
+images = pipe(prompt=prompt, num_inference_steps=4, guidance_scale=8.0).images
+```
+
+If you are using a later neuron compiler version, you can compile the checkpoint yourself with the following lines via [`🤗 optimum-neuron`](https://huggingface.co/docs/optimum-neuron/index) (the compilation takes approximately 40 min):
+
+```python
+from optimum.neuron import NeuronLatentConsistencyModelPipeline
+
+model_id = "SimianLuo/LCM_Dreamshaper_v7"
+num_images_per_prompt = 1
+input_shapes = {"batch_size": 1, "height": 768, "width": 768, "num_images_per_prompt": num_images_per_prompt}
+compiler_args = {"auto_cast": "matmul", "auto_cast_type": "bf16"}
+
+stable_diffusion = NeuronLatentConsistencyModelPipeline.from_pretrained(
+    model_id, export=True, **compiler_args, **input_shapes
+)
+save_directory = "lcm_sd_neuron/"
+stable_diffusion.save_pretrained(save_directory)
+
+# Push to hub
+stable_diffusion.push_to_hub(save_directory, repository_id="Jingya/LCM_Dreamshaper_v7_neuronx", use_auth_token=True)
+```
+
+And feel free to make a pull request and contribute to this repo, thx 🤗!