| --- |
| tags: |
| - text-to-image |
| - lora |
| - diffusers |
| - template:diffusion-lora |
| widget: |
| - output: |
| url: images/Screenshot from 2025-12-04 09-36-18.png |
| text: platypus |
| base_model: stable-diffusion-v1-5/stable-diffusion-v1-5 |
| instance_prompt: platypus |
| license: mit |
| language: |
| - en |
| pipeline_tag: text-to-image |
| library_name: diffusers |
| --- |
| # LoRA_platypus |
| |
| <Gallery /> |
| |
| |
| ## Trigger words |
| |
| You should use `platypus` to trigger the image generation. |
| |
| |
| ## Download model |
| |
| |
| [Download](/Mohan-diffuser/lora_platypus_sd_15/tree/main) them in the Files & versions tab. |
| |
| ```python |
| import torch |
| from diffusers import DiffusionPipeline,DDIMScheduler |
| import matplotlib.pyplot as plt |
| |
| # switch to "mps" for apple devices |
| pipeline = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") |
| pipeline.load_lora_weights("Mohan-diffuser/lora_platypus_sd_15") |
|
|
| pipeline.scheduler = DDIMScheduler.from_config(pipeline.scheduler.config) |
| |
| prompt = "platypus" |
| image = pipeline(prompt).images[0] |
| ``` |
| |
| |
| |
| ## Varying The LoRA Scale |
| ```python |
| gen_images=[] |
| lora_scales = [0.0,0.2,0.4,0.6,0.8,1.0,1.2,1.4] |
| for lora_scale in lora_scales: |
| gen_image = pipeline( |
| prompt="platypus", |
| guidance_scale=7.5, |
| num_inference_steps=25, |
| height=512, |
| width=512, |
| cross_attention_kwargs={"scale": lora_scale}, |
| generator=torch.manual_seed(0) |
| ).images[0] |
| |
| gen_images.append(gen_image) |
| |
| |
| fig,axes = plt.subplots(1,8,figsize=(20,10)) |
| for i,ax in enumerate(axes): |
| ax.imshow(gen_images[i]) |
| ax.set_title(f"lora_scale: {lora_scales[i]}") |
| ax.axis('off') |
| plt.show() |
| ``` |
| |
| ## Effect of different prompts |
|
|
| ```python |
| platypus_prompts = [ |
| "A cyberpunk platypus", |
| "A steampunk platypus with brass gears and mechanical limbs, intricate Victorian-style machinery, warm tones, highly detailed illustration", |
| "A platypus swimming in a serene river, soft watercolor painting, pastel colors, gentle brush strokes, dreamy atmosphere", |
| "Cute cartoon platypus, big expressive eyes, playful pose, bright cheerful colors, whimsical style, 2D animation style", |
| "A fantasy platypus wearing mystical armor, magical glowing runes on its body, standing on a cliff, dramatic lighting, epic fantasy illustration", |
| "A cybernetic platypus, robotic enhancements, glowing circuits, sci-fi aesthetic, sleek metallic textures, high detail, digital art", |
| "A platypus in the wild, painted in classical oil painting style, rich textures, dramatic lighting, realistic yet painterly, Baroque-inspired composition", |
| "A pop art platypus, vibrant contrasting colors, bold outlines, comic-style halftone patterns, playful modern art", |
| "A platypus rendered in retro pixel art, 16-bit video game style, colorful small-scale grid, cute and nostalgic", |
| "A surreal platypus floating in a dreamlike landscape, abstract shapes, vibrant colors, imaginative surrealism, Salvador Dali inspired" |
| ] |
| |
| gen_images=[] |
| |
| for prompt in platypus_prompts: |
| gen_image = pipeline( |
| prompt=prompt, |
| guidance_scale=7.5, |
| num_inference_steps=25, |
| height=512, |
| width=512, |
| cross_attention_kwargs={"scale": 0.9}, |
| generator=torch.manual_seed(42) |
| ).images[0] |
| |
| gen_images.append(gen_image) |
| |
| |
| fig,axes = plt.subplots(1,10,figsize=(20,10)) |
| for i,ax in enumerate(axes): |
| ax.imshow(gen_images[i]) |
| ax.axis('off') |
| plt.show() |
| ``` |
| ### Result |
|  |
