patrickvonplaten
commited on
Commit
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ae23482
1
Parent(s):
a032108
correct vocab
Browse files- load_lora.py +12 -0
- run_local.py +20 -17
load_lora.py
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#!/usr/bin/env python3
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import torch
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from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
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pipeline = StableDiffusionPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16, safety_checker=None
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).to("cuda")
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pipeline.scheduler = DPMSolverMultistepScheduler.from_config(
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pipeline.scheduler.config, use_karras_sigmas=True
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)
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pipeline.load_lora_weights("sayakpaul/sd-model-finetuned-lora-t4")
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run_local.py
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#!/usr/bin/env python3
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from diffusers import StableDiffusionPipeline
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import time
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import os
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from huggingface_hub import HfApi
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@@ -10,31 +10,34 @@ import requests
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from PIL import Image
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from io import BytesIO
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begin = ["a picture of <rickmann>", "a photo of <rickmann>", "<rickmann>", "an image of <rickmann>"]
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api = HfApi()
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start_time = time.time()
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path = "patrickvonplaten/papa_out_5"
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pipe = StableDiffusionPipeline.from_pretrained(path, safety_checker=None, torch_dtype=torch.float16)
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pipe = pipe.to("cuda")
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counter = 0
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for b in begin:
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for
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#!/usr/bin/env python3
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from diffusers import StableDiffusionPipeline, DDIMScheduler
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import time
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import os
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from huggingface_hub import HfApi
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from PIL import Image
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from io import BytesIO
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begin = ["a picture of <rickmann>", "a photo of <rickmann>", "The <rickmann>", "an image of <rickmann>"]
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mid = ["", " on a bike", " with sunglasses", " at the beach", " in front of a mountain", " in the water", " on a boat", " at a fashion show", " as a superstar model", " while it snows", " in a forest", " with a nice landscape"]
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end = ["", " , disco light style", ", minecraft style", " , picasso style", " as a lego person", ""]
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api = HfApi()
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start_time = time.time()
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path = "patrickvonplaten/papa_out_5"
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pipe = StableDiffusionPipeline.from_pretrained(path, safety_checker=None, torch_dtype=torch.float16)
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pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
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pipe = pipe.to("cuda")
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counter = 0
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for b in begin:
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for m in mid:
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for e in end:
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prompt = b + mid + e + ", highly realistic, super resolution, high quality photography, beautiful"
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images = pipe(prompt=prompt, num_images_per_prompt=2, eta=1.0, negative_prompt="ugly, bad quality, deformed", num_inference_steps=50).images
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for i, image in enumerate(images):
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path = os.path.join(Path.home(), "papa", f"{counter}.png")
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image.save(path)
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api.upload_file(
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path_or_fileobj=path,
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path_in_repo=path.split("/")[-1],
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repo_id="patrickvonplaten/papa",
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repo_type="dataset",
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)
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print(f"https://huggingface.co/datasets/patrickvonplaten/papa/blob/main/{counter}.png")
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counter += 1
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