---
license: apache-2.0
---

# Model Card for layer_xl_transparent_attn

<!-- Provide a quick summary of what the model is/does. -->

This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).

## Model Details

LoRA weights for SDXL using huggingface diffusers converted from this [weight](https://huggingface.co/LayerDiffusion/layerdiffusion-v1/resolve/main/layer_xl_transparent_attn.safetensors).

### Model Description

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- **Developed by:** Lvmin Zhang et al
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** SDXL LoRA-256
- **Language(s) (NLP):** [More Information Needed]
- **License:** Apache 2.0
- **Finetuned from model [optional]:** SDXL

### Model Sources [optional]

<!-- Provide the basic links for the model. -->

- **Repository:** https://github.com/layerdiffusion/LayerDiffuse
- **Paper [optional]:** https://arxiv.org/abs/2402.17113
- **Demo [optional]:** [More Information Needed]

## Uses

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### Direct Use

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[More Information Needed]

### Downstream Use [optional]

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### Out-of-Scope Use

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## Bias, Risks, and Limitations

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[More Information Needed]

### Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

```bash
from diffusers import StableDiffusionXLPipeline
from huggingface_hub import hf_hub_download
from safetensors.torch import load_file

pipe = StableDiffusionXLPipeline.from_pretrained(
  "stabilityai/stable-diffusion-xl-base-1.0",
  use_safetensors=True, 
  variant="fp16",
  torch_dtype=torch.float16, 
)
# pipe.enable_xformers_memory_efficient_attention()
pipe.to("cuda")

pipe.load_lora_weights(hf_hub_download("gxkok/layer-diffusion-xl-transparent-attn-lora", "pytorch_lora_weights.safetensors"))
```

[More Information Needed]

## Training Details

### Training Data

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[More Information Needed]

### Training Procedure

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#### Preprocessing [optional]

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#### Training Hyperparameters

- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

#### Speeds, Sizes, Times [optional]

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[More Information Needed]

## Evaluation

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### Testing Data, Factors & Metrics

#### Testing Data

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[More Information Needed]

#### Factors

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#### Metrics

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### Results

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#### Summary



## Model Examination [optional]

<!-- Relevant interpretability work for the model goes here -->

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## Environmental Impact

<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->

Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]

## Technical Specifications [optional]

### Model Architecture and Objective

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### Compute Infrastructure

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#### Hardware

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#### Software

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## Citation [optional]

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**BibTeX:**

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**APA:**

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## Glossary [optional]

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## More Information [optional]

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## Model Card Authors [optional]

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## Model Card Contact

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