--- language: - en license: other license_name: flux-1-dev-non-commercial-license license_link: LICENSE.md tags: - safetensors - pruna-ai extra_gated_prompt: By clicking "Agree", you agree to the [FluxDev Non-Commercial License Agreement](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md) and acknowledge the [Acceptable Use Policy](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/POLICY.md). --- # Model Card for LenSch/caching_only 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. ## Usage First things first, you need to install the pruna library: ```bash pip install pruna ``` You can [use the library_name library to load the model](https://huggingface.co/LenSch/caching_only?library=library_name) but this might not include all optimizations by default. To ensure that all optimizations are applied, use the pruna library to load the model using the following code: ```python from pruna import PrunaModel loaded_model = PrunaModel.from_pretrained( "LenSch/caching_only" ) # we can then run inference using the methods supported by the base model ``` Alternatively, you can visit [the Pruna documentation](https://docs.pruna.ai/en/stable/) for more information. ## Smash Configuration The compression configuration of the model is stored in the `smash_config.json` file, which describes the optimization methods that were applied to the model. ```bash { "batcher": null, "cacher": "fora", "compiler": "stable_fast", "factorizer": null, "kernel": null, "pruner": null, "quantizer": null, "fora_interval": 4, "fora_start_step": 1, "batch_size": 1, "device": "cuda:0", "device_map": null, "save_fns": [ "save_before_apply" ], "load_fns": [ "diffusers" ], "reapply_after_load": { "factorizer": null, "pruner": null, "quantizer": null, "kernel": null, "cacher": "fora", "compiler": "stable_fast", "batcher": null } } ``` ## 🌍 Join the Pruna AI community! [![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/JFQmtFKCjd) [![Reddit](https://img.shields.io/reddit/subreddit-subscribers/PrunaAI?style=social)](https://www.reddit.com/r/PrunaAI/)