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language:
- en
license: apache-2.0
pipeline_tag: image-to-image
tags:
- pruna-ai
- safetensors
---
# Model Card for PrunaAI/flux2-klein-4b-optimized-smashed
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/PrunaAI/flux2-klein-4b-optimized-smashed?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(
"PrunaAI/flux2-klein-4b-optimized-smashed"
)
# 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
{
"awq": false,
"c_generate": false,
"c_translate": false,
"c_whisper": false,
"deepcache": false,
"diffusers_int8": false,
"fastercache": false,
"flash_attn3": false,
"fora": true,
"gptq": false,
"half": false,
"hqq": false,
"hqq_diffusers": false,
"hyper": false,
"ifw": false,
"img2img_denoise": false,
"ipex_llm": false,
"llm_int8": false,
"moe_kernel_tuner": false,
"pab": false,
"padding_pruning": false,
"qkv_diffusers": false,
"quanto": false,
"realesrgan_upscale": false,
"reduce_noe": false,
"ring_attn": false,
"sage_attn": false,
"stable_fast": false,
"text_to_image_distillation_inplace_perp": false,
"text_to_image_distillation_lora": false,
"text_to_image_distillation_perp": false,
"text_to_image_inplace_perp": false,
"text_to_image_lora": false,
"text_to_image_perp": false,
"text_to_text_inplace_perp": false,
"text_to_text_lora": false,
"text_to_text_perp": false,
"torch_compile": true,
"torch_dynamic": false,
"torch_structured": false,
"torch_unstructured": false,
"torchao": true,
"whisper_s2t": false,
"x_fast": false,
"zipar": false,
"fora_backbone_calls_per_step": 2,
"fora_interval": 3,
"fora_start_step": 4,
"torch_compile_backend": "inductor",
"torch_compile_dynamic": null,
"torch_compile_fullgraph": false,
"torch_compile_make_portable": false,
"torch_compile_max_kv_cache_size": 400,
"torch_compile_mode": "default",
"torch_compile_seqlen_manual_cuda_graph": 100,
"torch_compile_target": "model",
"torchao_excluded_modules": "none",
"torchao_quant_type": "fp8wo",
"torchao_target_modules": {
"include": [
"*single_transformer_blocks.*"
],
"exclude": [
"pe_embedder",
"*norm*",
"*embed*"
]
},
"batch_size": 1,
"device": "cuda",
"device_map": null,
"save_fns": [
"save_before_apply",
"save_before_apply"
],
"save_artifacts_fns": [],
"load_fns": [
"diffusers"
],
"load_artifacts_fns": [],
"reapply_after_load": {
"torchao": true,
"fora": true,
"torch_compile": true
}
}
```
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