Upload folder using huggingface_hub (#1)

- d9eef1a48f22b0f29c1c11a2e919dc324ce201d62fc63acfea2a55f41a1f6f30 (90f87700c459ebc02ea2e91624dcc9df6bcedc27)
- 2c04f283d5f0695dd7d235bf6590cb885b3fb1d0384d349a5af1f1ef82733b02 (547a642030a194ff5105dfbfa4c32cc65e90af49)

README.md

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+---
+license: apache-2.0
+library_name: pruna-engine
+thumbnail: "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"
+metrics:
+- memory_disk
+- memory_inference
+- inference_latency
+- inference_throughput
+- inference_CO2_emissions
+- inference_energy_consumption
+---
+<!-- header start -->
+<!-- 200823 -->
+<div style="width: auto; margin-left: auto; margin-right: auto">
+    <a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer">
+        <img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
+    </a>
+</div>
+<!-- header end -->
+
+[![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)
+[![Discord](https://img.shields.io/badge/Discord-Join%20Us-blue?style=social&logo=discord)](https://discord.gg/CP4VSgck)
+
+# Simply make AI models cheaper, smaller, faster, and greener!
+
+- 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/)
+- Join Pruna AI community on Discord [here](https://discord.gg/CP4VSgck) to share feedback/suggestions or get help.
+
+## Results
+
+![image info](./plots.png)
+
+**Important remarks:**
+- The quality of the model output might slightly vary compared to the base model. There might be minimal quality loss.
+- These results were obtained on NVIDIA A100-PCIE-40GB with configuration described in config.json and are obtained after a hardware warmup. Efficiency results may vary in other settings (e.g. other hardware, image size, batch size, ...).
+- You can request premium access to more compression methods and tech support for your specific use-cases [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai).
+
+## Setup
+
+You can run the smashed model with these steps:
+
+0. Check cuda, torch, packaging requirements are installed. For cuda, check with `nvcc --version` and install with `conda install nvidia/label/cuda-12.1.0::cuda`. For packaging and torch, run `pip install packaging torch`.
+1. Install the `pruna-engine` available [here](https://pypi.org/project/pruna-engine/) on Pypi. It might take 15 minutes to install.
+    ```bash
+   pip install pruna-engine[gpu] --extra-index-url https://pypi.nvidia.com --extra-index-url https://pypi.ngc.nvidia.com --extra-index-url https://prunaai.pythonanywhere.com/
+    ```
+3. Download the model files using one of these three options. 
+   - Option 1 - Use command line interface (CLI):
+       ```bash
+       mkdir Linaqruf-animagine-xl-turbo-tiny-green-smashed
+       huggingface-cli download PrunaAI/Linaqruf-animagine-xl-turbo-tiny-green-smashed --local-dir Linaqruf-animagine-xl-turbo-tiny-green-smashed --local-dir-use-symlinks False
+       ```
+   - Option 2 - Use Python:
+       ```python
+       import subprocess
+       repo_name = "Linaqruf-animagine-xl-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 = "Linaqruf-animagine-xl-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.
+    ```
+
+## Configurations
+
+The configuration info are in `config.json`.
+
+## Credits & License
+
+We follow the same license as the original model. Please check the license of the original model Linaqruf/animagine-xl before using this model which provided the base model.
+
+## Want to compress other models?
+
+- 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).

config.json

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+{"pruners": "None", "pruning_ratio": "None", "factorizers": "None", "quantizers": "None", "n_quantization_bits": 32, "output_deviation": 0.0, "compilers": "['step_caching', 'tiling', 'diffusers2']", "static_batch": true, "static_shape": false, "controlnet": "None", "unet_dim": 4, "device": "cuda", "batch_size": 1, "max_batch_size": 1, "image_height": 1024, "image_width": 1024, "version": "xl-1.0", "scheduler": "DDIM", "task": "txt2imgxl", "weight_name": "None", "model_name": "Linaqruf/animagine-xl", "save_load_fn": "stable_fast"}

model/optimized_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2d7ee49e14de6a3413050b4a09947e392fa5cb8beac69fb7a175807bf99363c2
+size 6943178621

model/smash_config.json

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+{"api_key": "pruna_c4c77860c62a2965f6bc281841ee1d7bd3", "verify_url": "http://johnrachwan.pythonanywhere.com", "smash_config": {"pruners": "None", "pruning_ratio": "None", "factorizers": "None", "quantizers": "None", "n_quantization_bits": 32, "output_deviation": 0.0, "compilers": "['step_caching', 'tiling', 'diffusers2']", "static_batch": true, "static_shape": false, "controlnet": "None", "unet_dim": 4, "device": "cuda", "cache_dir": ".models/optimized_model", "batch_size": 1, "max_batch_size": 1, "image_height": 1024, "image_width": 1024, "version": "xl-1.0", "scheduler": "DDIM", "task": "txt2imgxl", "weight_name": "None", "model_name": "Linaqruf/animagine-xl", "save_load_fn": "stable_fast"}}