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Browse files- README.md +8 -4
- smash_config.json +5 -1
README.md
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- pruna_pro-ai
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---
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# Model Card for
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This model was created using the [pruna](https://github.com/PrunaAI/pruna) library. Pruna is a model optimization framework built for developers, enabling you to deliver more efficient models with minimal implementation overhead.
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pip install pruna_pro
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```
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You can [use the diffusers library to load the model](https://huggingface.co/
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To ensure that all optimizations are applied, use the pruna library to load the model using the following code:
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from pruna_pro import PrunaProModel
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loaded_model = PrunaProModel.from_pretrained(
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"
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)
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# we can then run inference using the methods supported by the base model
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```
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"batcher": null,
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"cacher": null,
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"compiler": null,
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"distiller": null,
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"distributer": null,
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"enhancer": null,
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"pruner": null,
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"quantizer": null,
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"recoverer": null,
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"batch_size": 1,
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"device": "cpu",
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"device_map": null,
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"distiller": null,
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"kernel": null,
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"cacher": null,
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"recoverer": null,
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"distributer": null,
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"compiler": null,
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"enhancer": null
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}
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}
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```
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- pruna_pro-ai
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---
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# Model Card for pruna-test/test-save-tiny-stable-diffusion-pipe-smashed-pro
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This model was created using the [pruna](https://github.com/PrunaAI/pruna) library. Pruna is a model optimization framework built for developers, enabling you to deliver more efficient models with minimal implementation overhead.
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pip install pruna_pro
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```
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You can [use the diffusers library to load the model](https://huggingface.co/pruna-test/test-save-tiny-stable-diffusion-pipe-smashed-pro?library=diffusers) but this might not include all optimizations by default.
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To ensure that all optimizations are applied, use the pruna library to load the model using the following code:
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from pruna_pro import PrunaProModel
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loaded_model = PrunaProModel.from_pretrained(
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"pruna-test/test-save-tiny-stable-diffusion-pipe-smashed-pro"
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)
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# we can then run inference using the methods supported by the base model
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```
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"batcher": null,
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"cacher": null,
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"compiler": null,
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"decoder": null,
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"distiller": null,
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"distributer": null,
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"enhancer": null,
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"pruner": null,
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"quantizer": null,
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"recoverer": null,
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"resampler": null,
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"batch_size": 1,
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"device": "cpu",
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"device_map": null,
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"distiller": null,
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"kernel": null,
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"resampler": null,
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"recoverer": null,
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"enhancer": null,
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"decoder": null
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}
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}
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```
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smash_config.json
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"device": "cpu",
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"device": "cpu",
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"decoder": null
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}
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}
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