pruna-test/test-save-tiny-stable-diffusion-pipe-smashed-pro
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1---2library_name: diffusers3tags:4- safetensors5- pruna-ai6- pruna_pro-ai7---8 9# Model Card for pruna-test/test-save-tiny-stable-diffusion-pipe-smashed-pro10 11This 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.12 13## Usage14 15First things first, you need to install the pruna library:16 17```bash18pip install pruna_pro19```20 21You 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.22 23To ensure that all optimizations are applied, use the pruna library to load the model using the following code:24 25```python26from pruna_pro import PrunaProModel27 28loaded_model = PrunaProModel.from_pretrained(29 "pruna-test/test-save-tiny-stable-diffusion-pipe-smashed-pro"30)31# we can then run inference using the methods supported by the base model32```33 34 35For inference, you can use the inference methods of the original model like shown in [the original model card](https://huggingface.co/hf-internal-testing/tiny-stable-diffusion-pipe?library=diffusers).36 Alternatively, you can visit [the Pruna documentation](https://docs.pruna.ai/en/stable/) for more information.37 38## Smash Configuration39 40The compression configuration of the model is stored in the `smash_config.json` file, which describes the optimization methods that were applied to the model.41 42```bash43{44 "adaptive": false,45 "auto": false,46 "awq": false,47 "bottleneck": false,48 "c_generate": false,49 "c_translate": false,50 "c_whisper": false,51 "deepcache": false,52 "diffusers_higgs": false,53 "diffusers_int8": false,54 "fastercache": false,55 "flash_attn3": false,56 "flux_caching": false,57 "fora": false,58 "fp4": false,59 "fp8": false,60 "gptq": false,61 "half": false,62 "higgs": false,63 "hqq": false,64 "hqq_diffusers": false,65 "hyper": false,66 "ifw": false,67 "img2img_denoise": false,68 "kvpress": false,69 "llama_cpp": false,70 "llm_int8": false,71 "moe_kernel_tuner": false,72 "pab": false,73 "padding_pruning": false,74 "periodic": false,75 "prores": false,76 "qkv_diffusers": false,77 "quanto": false,78 "radial_attn": false,79 "realesrgan_upscale": false,80 "reduce_noe": false,81 "ring_attn": false,82 "sage_attn": false,83 "stable_fast": false,84 "static_fp8_diffusers": false,85 "taylor": false,86 "taylor_auto": false,87 "text_to_image_distillation_inplace_perp": false,88 "text_to_image_distillation_lora": false,89 "text_to_image_distillation_perp": false,90 "text_to_image_inplace_perp": false,91 "text_to_image_lora": false,92 "text_to_image_perp": false,93 "text_to_text_inplace_perp": false,94 "text_to_text_lora": false,95 "text_to_text_perp": false,96 "time_aware_fp8_diffusers": false,97 "token_merging": false,98 "torch_compile": false,99 "torch_dynamic": false,100 "torch_structured": false,101 "torch_unstructured": false,102 "torchao": false,103 "torchao_autoquant": false,104 "x_fast": false,105 "zipar": false,106 "batch_size": 1,107 "device": "cpu",108 "device_map": null,109 "save_fns": [],110 "save_artifacts_fns": [],111 "load_fns": [112 "diffusers"113 ],114 "load_artifacts_fns": [],115 "reapply_after_load": {}116}117```118 119## 🌍 Join the Pruna AI community!120 121[](https://twitter.com/PrunaAI)122[](https://github.com/PrunaAI)123[](https://www.linkedin.com/company/93832878/admin/feed/posts/?feedType=following)124[](https://discord.gg/JFQmtFKCjd)125[](https://www.reddit.com/r/PrunaAI/)