# INFO
This is checkpoint based on [stabilityai/stable-diffusion-2-1](https://huggingface.co/stabilityai/stable-diffusion-2-1/blob/main/v2-1_768-nonema-pruned.safetensors) and [logo-wizard/logo-diffusion](https://huggingface.co/logo-wizard/logo-diffusion). The weights were fine-tuned on the [logo-wizard/modern-logo-dataset](https://huggingface.co/datasets/logo-wizard/modern-logo-dataset) dataset. You can find some example images in the following. 

# Best practices
We recommend using this model with the following prompt template:  
**positive:** f"a logo of {company industry}, {some objects}, {colors}, modern, minimalism, vector art, 2d, best quality, centered"  
**negative:** "low quality, worst quality, bad composition, extra digit, fewer digits, text, inscription, watermark, label, asymmetric"  
  
Some other recommendations:  
**num_inference_steps** = *30*  
**guidance_scale** = *7.5*  
**height** = *768*  
**width** = *768*  
**scheduler** = diffusers.EulerAncestralDiscreteScheduler (used by default)

![results](./results.png)
{"license": "creativeml-openrail-m", "tags": ["text-to-image", "lora", "stable-diffusion"], "datasets": ["logo-wizard/modern-logo-dataset"], "pipeline_tag": "text-to-image"}
diffusers text-to-image lora stable-diffusion dataset:logo-wizard/modern-logo-dataset license:creativeml-openrail-m endpoints_compatible has_space diffusers:StableDiffusionPipeline region:us
TAGS
#diffusers #text-to-image #lora #stable-diffusion #dataset-logo-wizard/modern-logo-dataset #license-creativeml-openrail-m #endpoints_compatible #has_space #diffusers-StableDiffusionPipeline #region-us 

# INFO
This is checkpoint based on stabilityai/stable-diffusion-2-1 and logo-wizard/logo-diffusion. The weights were fine-tuned on the logo-wizard/modern-logo-dataset dataset. You can find some example images in the following. 

# Best practices
We recommend using this model with the following prompt template:  
positive: f"a logo of {company industry}, {some objects}, {colors}, modern, minimalism, vector art, 2d, best quality, centered"  
negative: "low quality, worst quality, bad composition, extra digit, fewer digits, text, inscription, watermark, label, asymmetric"  
  
Some other recommendations:  
num_inference_steps = *30*  
guidance_scale = *7.5*  
height = *768*  
width = *768*  
scheduler = diffusers.EulerAncestralDiscreteScheduler (used by default)

!results
# INFO
This is checkpoint based on stabilityai/stable-diffusion-2-1 and logo-wizard/logo-diffusion. The weights were fine-tuned on the logo-wizard/modern-logo-dataset dataset. You can find some example images in the following. # Best practices
We recommend using this model with the following prompt template:  
positive: f"a logo of {company industry}, {some objects}, {colors}, modern, minimalism, vector art, 2d, best quality, centered"  
negative: "low quality, worst quality, bad composition, extra digit, fewer digits, text, inscription, watermark, label, asymmetric"  
  
Some other recommendations:  
num_inference_steps = *30*  
guidance_scale = *7.5*  
height = *768*  
width = *768*  
scheduler = diffusers.EulerAncestralDiscreteScheduler (used by default)

!results
TAGS
#diffusers #text-to-image #lora #stable-diffusion #dataset-logo-wizard/modern-logo-dataset #license-creativeml-openrail-m #endpoints_compatible #has_space #diffusers-StableDiffusionPipeline #region-us 
 # INFO
This is checkpoint based on stabilityai/stable-diffusion-2-1 and logo-wizard/logo-diffusion. The weights were fine-tuned on the logo-wizard/modern-logo-dataset dataset. You can find some example images in the following. # Best practices
We recommend using this model with the following prompt template:  
positive: f"a logo of {company industry}, {some objects}, {colors}, modern, minimalism, vector art, 2d, best quality, centered"  
negative: "low quality, worst quality, bad composition, extra digit, fewer digits, text, inscription, watermark, label, asymmetric"  
  
Some other recommendations:  
num_inference_steps = *30*  
guidance_scale = *7.5*  
height = *768*  
width = *768*  
scheduler = diffusers.EulerAncestralDiscreteScheduler (used by default)

!results