8bf42fcb99c03b97929a9b217e8d513edff55a95671eb98f18edba08fc5103d0
Browse files- README.md +1 -1
- config.json +1 -1
- model/smash_config.json +1 -1
- plots.png +0 -0
README.md
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@@ -48,7 +48,7 @@ You can run the smashed model with these steps:
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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`.
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1. Install the `pruna-engine` available [here](https://pypi.org/project/pruna-engine/) on Pypi. It might take 15 minutes to install.
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```bash
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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/
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```
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3. Download the model files using one of these three options.
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- Option 1 - Use command line interface (CLI):
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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`.
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1. Install the `pruna-engine` available [here](https://pypi.org/project/pruna-engine/) on Pypi. It might take 15 minutes to install.
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```bash
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pip install pruna-engine[gpu]==0.6.0 --extra-index-url https://pypi.nvidia.com --extra-index-url https://pypi.ngc.nvidia.com --extra-index-url https://prunaai.pythonanywhere.com/
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```
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3. Download the model files using one of these three options.
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- Option 1 - Use command line interface (CLI):
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config.json
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{"pruners": "None", "pruning_ratio":
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{"pruners": "None", "pruning_ratio": 0.0, "factorizers": "None", "quantizers": "None", "n_quantization_bits": 32, "output_deviation": 0.005, "compilers": "['diffusers2', 'tiling', 'step_caching']", "static_batch": true, "static_shape": false, "controlnet": "None", "unet_dim": 4, "device": "cuda", "batch_size": 1, "max_batch_size": 1, "image_height": 512, "image_width": 512, "version": "1.5", "task": "txt2img", "model_name": "nitrosocke/Arcane-Diffusion", "weight_name": "None", "save_load_fn": "stable_fast"}
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model/smash_config.json
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{"api_key": "pruna_c4c77860c62a2965f6bc281841ee1d7bd3", "verify_url": "http://johnrachwan.pythonanywhere.com", "smash_config": {"pruners": "None", "pruning_ratio":
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{"api_key": "pruna_c4c77860c62a2965f6bc281841ee1d7bd3", "verify_url": "http://johnrachwan.pythonanywhere.com", "smash_config": {"pruners": "None", "pruning_ratio": 0.0, "factorizers": "None", "quantizers": "None", "n_quantization_bits": 32, "output_deviation": 0.005, "compilers": "['diffusers2', 'tiling', 'step_caching']", "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": 512, "image_width": 512, "version": "1.5", "task": "txt2img", "model_name": "nitrosocke/Arcane-Diffusion", "weight_name": "None", "save_load_fn": "stable_fast"}}
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plots.png
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