44af34a5ae1837f27a7342bb030dd2e51b5c68142f5cbab28ae172ce7ee5d276

README.md

@@ -21,30 +21,52 @@ metrics:
 
 # Simply make AI models cheaper, smaller, faster, and greener!
 
+[![Twitter](https://img.shields.io/twitter/follow/PrunaAI?style=social)](https://twitter.com/PrunaAI)
+[![GitHub](https://img.shields.io/github/followers/PrunaAI?label=Follow%20%40PrunaAI&style=social)](https://github.com/PrunaAI)
+[![LinkedIn](https://img.shields.io/badge/LinkedIn-Connect-blue)](https://www.linkedin.com/company/93832878/admin/feed/posts/?feedType=following)
+
+- Give a thumbs up if you like this model!
+- Contact us and tell us which model to compress next [here](https://www.pruna.ai/contact).
+- Request access to easily compress your *own* AI models [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai).
+- Read the documentations to know more [here](https://pruna-ai-pruna.readthedocs-hosted.com/en/latest/)
+- Share feedback and suggestions on the Slack of Pruna AI (Coming soon!).
+
 ## Results
 
 ![image info](./plots.png)
 
+These results were obtained on NVIDIA A100-PCIE-40GB with configuration described in config.json. Results may vary in other settings (e.g. other hardware, image size, batch size, ...).
+
 ## Setup
 
-You can run the smashed model by:
-1. Installing and importing the `pruna-engine` (version 0.2.9) package. Use `pip install pruna-engine==0.2.9 --extra-index-url https://pypi.nvidia.com --extra-index-url https://pypi.ngc.nvidia.com` for installation. See [Pypi](https://pypi.org/project/pruna-engine/) for details on the package.
-2. Downloading the model files. This can be done using the Hugging Face CLI with the following commands:
+You can run the smashed model with these steps:
+0. Check that you have cuda installed. You can do this by running `nvcc --version` or `conda install nvidia/label/cuda-12.1.0::cuda`.
+1. Install the `pruna-engine` available [here](https://pypi.org/project/pruna-engine/) on Pypi. It might take 15 minutes to install.
     ```bash
-    mkdir CompVis-stable-diffusion-v1-4-smashed
-    huggingface-cli download PrunaAI/CompVis-stable-diffusion-v1-4-turbo-tiny-green-smashed --local-dir CompVis-stable-diffusion-v1-4-turbo-tiny-green-smashed --local-dir-use-symlinks False
+   pip install pruna-engine[gpu] --extra-index-url https://pypi.nvidia.com --extra-index-url https://pypi.ngc.nvidia.com
+    ```
+3. Download the model files using one of these three options. 
+   - Option 1 - Use command line interface (CLI):
+       ```bash
+       mkdir CompVis-stable-diffusion-v1-4-turbo-tiny-green-smashed
+       huggingface-cli download PrunaAI/CompVis-stable-diffusion-v1-4-turbo-tiny-green-smashed --local-dir CompVis-stable-diffusion-v1-4-turbo-tiny-green-smashed --local-dir-use-symlinks False
+       ```
+   - Option 2 - Use Python:
+       ```python
+       import subprocess
+       repo_name = "CompVis-stable-diffusion-v1-4-turbo-tiny-green-smashed"
+       subprocess.run(["mkdir", repo_name])
+       subprocess.run(["huggingface-cli", "download", 'PrunaAI/'+ repo_name, "--local-dir", repo_name, "--local-dir-use-symlinks", "False"])
+       ```
+   - Option 3 - Download them manually on the HuggingFace model page.
+3. Load & run the model.
+    ```python
+    from pruna_engine.PrunaModel import PrunaModel
+   
+    model_path = "CompVis-stable-diffusion-v1-4-turbo-tiny-green-smashed/model"  # Specify the downloaded model path.
+    smashed_model = PrunaModel.load_model(model_path)  # Load the model.
+    smashed_model(prompt='Beautiful fruits in trees', height=1024, width=1024)[0][0]  # Run the model where x is the expected input of.
     ```
-   Alternatively, you can download them manually.
-3. Loading the model.
-4. Running the model.
-You can achieve this by running the following code:
-
-```python
-from pruna_engine.PrunaModel import PrunaModel  # Step (1): install and import `pruna-engine` package.
-model_path = "CompVis-stable-diffusion-v1-4-turbo-tiny-green-smashed/model" # Step (2): specify the downloaded model path.
-smashed_model = PrunaModel.load_model(model_path)  # Step (3): load the model.
-y = smashed_model(prompt="a silly prune with a face in high definition", image_height=512, image_width=512)[0]  # Step (4): run the model.
-```
 
 ## Configurations
 
@@ -52,7 +74,7 @@ The configuration info are in `config.json`.
 
 ## License
 
-We follow the same license as the original model. Please check the license of the original model before using this model.
+We follow the same license as the original model. Please check the license of the original model ORIGINAL_CompVis-stable-diffusion-v1-4-turbo-tiny-green-smashed before using this model.
 
 ## Want to compress other models?
 

config.json

@@ -1 +1 @@
-{"pruner": "None", "pruning_ratio": 0.0, "factorizer": "None", "quantizer": "None", "n_quantization_bits": 32, "output_deviation": 0.005, "compiler": "diffusers", "static_batch": true, "static_shape": true, "controlnet": "None", "unet_dim": 4, "max_batch_size": 1, "image_height": 512, "image_width": 512, "version": "1.4"}
+{"pruners": "None", "pruning_ratio": 0.0, "factorizers": "None", "quantizers": "None", "n_quantization_bits": 32, "output_deviation": 0.005, "compilers": "['diffusers2']", "static_batch": true, "static_shape": false, "controlnet": "None", "unet_dim": 4, "device": "cuda", "save_dir": "/ceph/hdd/staff/charpent/models/.models/optimized_model", "batch_size": 1, "max_batch_size": 1, "image_height": 512, "image_width": 512, "version": "1.4", "task": "txt2img", "model_name": "CompVis/stable-diffusion-v1-4", "weight_name": "None", "save_load_fn": "stable_fast"}

model/smash_config.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d7f0574c6dbd9fe6b9bd3099a09b2ae640474eeee1bda5334f039f54bbdae188
+size 742