Prompt
stringlengths 1
389
| Category
stringclasses 12
values | Challenge
stringclasses 11
values | Note
stringclasses 24
values | images
imagewidth (px) 256
256
| model_name
stringclasses 1
value | seed
int64 0
0
|
---|---|---|---|---|---|---|
bond | Abstract | Basic | Biology-inspired concepts with multiple meanings | openMUSE/muse-256 | 0 |
|
element | Abstract | Basic | Biology-inspired concepts with multiple meanings | openMUSE/muse-256 | 0 |
|
molecule | Abstract | Basic | Biology-inspired concepts with multiple meanings | openMUSE/muse-256 | 0 |
|
life | Abstract | Basic | Biology-inspired concepts with multiple meanings | openMUSE/muse-256 | 0 |
|
protein | Abstract | Basic | Biology-inspired concepts with multiple meanings | openMUSE/muse-256 | 0 |
|
yin-yang | Abstract | Basic | Related to five elements | openMUSE/muse-256 | 0 |
|
wood | Abstract | Basic | Related to five elements | openMUSE/muse-256 | 0 |
|
metal | Abstract | Basic | Related to five elements | openMUSE/muse-256 | 0 |
|
space | Abstract | Basic | Related to five elements | openMUSE/muse-256 | 0 |
|
air | Abstract | Basic | Related to five elements | openMUSE/muse-256 | 0 |
|
fire | Abstract | Basic | Related to five elements | openMUSE/muse-256 | 0 |
|
water | Abstract | Basic | Related to five elements | openMUSE/muse-256 | 0 |
|
earth | Abstract | Basic | Related to five elements | openMUSE/muse-256 | 0 |
|
force | Abstract | Basic | Physics concepts | openMUSE/muse-256 | 0 |
|
motion | Abstract | Basic | Physics concepts | openMUSE/muse-256 | 0 |
|
inertia | Abstract | Basic | Physics concepts | openMUSE/muse-256 | 0 |
|
energy | Abstract | Basic | Physics concepts | openMUSE/muse-256 | 0 |
|
black hole | Abstract | Basic | Physics concepts | openMUSE/muse-256 | 0 |
|
gravity | Abstract | Basic | Physics concepts | openMUSE/muse-256 | 0 |
|
peace | Abstract | Basic | null | openMUSE/muse-256 | 0 |
|
fairness | Abstract | Basic | null | openMUSE/muse-256 | 0 |
|
gender | Abstract | Basic | null | openMUSE/muse-256 | 0 |
|
intelligence | Abstract | Basic | null | openMUSE/muse-256 | 0 |
|
bias | Abstract | Basic | null | openMUSE/muse-256 | 0 |
|
hate | Abstract | Basic | null | openMUSE/muse-256 | 0 |
|
anger | Abstract | Basic | null | openMUSE/muse-256 | 0 |
|
emotion | Abstract | Basic | null | openMUSE/muse-256 | 0 |
|
feeling | Abstract | Basic | null | openMUSE/muse-256 | 0 |
|
love | Abstract | Basic | null | openMUSE/muse-256 | 0 |
|
artificial intelligence | Abstract | Basic | null | openMUSE/muse-256 | 0 |
|
meaning of life | Abstract | Basic | null | openMUSE/muse-256 | 0 |
|
42 | Abstract | Basic | Simple numbers but challenging | openMUSE/muse-256 | 0 |
|
0 | Abstract | Basic | Simple numbers but challenging | openMUSE/muse-256 | 0 |
|
infinity | Abstract | Basic | Math concepts | openMUSE/muse-256 | 0 |
|
imaginary numbers | Abstract | Basic | Math concepts | openMUSE/muse-256 | 0 |
|
Fibonacci number | Abstract | Basic | Math concepts | openMUSE/muse-256 | 0 |
|
golden ratio | Abstract | Basic | Math concepts | openMUSE/muse-256 | 0 |
|
an F1 | Vehicles | Basic | null | openMUSE/muse-256 | 0 |
|
parallel lines | Illustrations | Basic | Math concepts | openMUSE/muse-256 | 0 |
|
concentric circles | Illustrations | Basic | Math concepts | openMUSE/muse-256 | 0 |
|
concurrent lines | Illustrations | Basic | Math concepts | openMUSE/muse-256 | 0 |
|
congruent triangles | Illustrations | Basic | Math concepts | openMUSE/muse-256 | 0 |
|
a hot air balloon | Vehicles | Basic | null | openMUSE/muse-256 | 0 |
|
The Starry Night | Arts | Basic | null | openMUSE/muse-256 | 0 |
|
300 | Abstract | Basic | Simple numbers but challenging | openMUSE/muse-256 | 0 |
|
101 | Abstract | Basic | Simple numbers but challenging | openMUSE/muse-256 | 0 |
|
U.S. 101 | World Knowledge | Basic | Simple numbers but challenging | openMUSE/muse-256 | 0 |
|
commonsense | Abstract | Basic | null | openMUSE/muse-256 | 0 |
|
happiness | Abstract | Basic | null | openMUSE/muse-256 | 0 |
|
hope | Abstract | Basic | null | openMUSE/muse-256 | 0 |
|
insight | Abstract | Basic | null | openMUSE/muse-256 | 0 |
|
inspiration | Abstract | Basic | null | openMUSE/muse-256 | 0 |
|
derision | Abstract | Basic | null | openMUSE/muse-256 | 0 |
|
Salvador Dalí | People | Basic | null | openMUSE/muse-256 | 0 |
|
a shiba inu | Animals | Basic | null | openMUSE/muse-256 | 0 |
|
a handpalm | People | Basic | null | openMUSE/muse-256 | 0 |
|
an espresso machine | Artifacts | Basic | null | openMUSE/muse-256 | 0 |
|
a propaganda poster | Artifacts | Basic | null | openMUSE/muse-256 | 0 |
|
The Oriental Pearl | World Knowledge | Basic | CogView | openMUSE/muse-256 | 0 |
|
Ha Long Bay | World Knowledge | Basic | null | openMUSE/muse-256 | 0 |
|
A Vietnam map | World Knowledge | Basic | null | openMUSE/muse-256 | 0 |
|
A bowl of Pho | Food & Beverage | Basic | null | openMUSE/muse-256 | 0 |
|
a snail | Animals | Basic | null | openMUSE/muse-256 | 0 |
|
brain coral | Animals | Basic | null | openMUSE/muse-256 | 0 |
|
a walnut | Produce & Plants | Basic | null | openMUSE/muse-256 | 0 |
|
a capybara | Animals | Basic | null | openMUSE/muse-256 | 0 |
|
a baby penguin | Animals | Basic | null | openMUSE/muse-256 | 0 |
|
a cup of boba | Food & Beverage | Basic | null | openMUSE/muse-256 | 0 |
|
a photo of san francisco's golden gate bridge | World Knowledge | Basic | DALL-E | openMUSE/muse-256 | 0 |
|
A picture of some food in the plate | Food & Beverage | Basic | VQ-Diffusion | openMUSE/muse-256 | 0 |
|
a chair | Artifacts | Basic | null | openMUSE/muse-256 | 0 |
|
the Empire State Building | World Knowledge | Basic | null | openMUSE/muse-256 | 0 |
|
the Sydney Opera House | World Knowledge | Basic | null | openMUSE/muse-256 | 0 |
|
a hedgehog | Animals | Basic | null | openMUSE/muse-256 | 0 |
|
a corgi | Animals | Basic | null | openMUSE/muse-256 | 0 |
|
a robot | Artifacts | Basic | null | openMUSE/muse-256 | 0 |
|
robots | Artifacts | Basic | null | openMUSE/muse-256 | 0 |
|
a fall landscape | Outdoor Scenes | Basic | null | openMUSE/muse-256 | 0 |
|
a sunset | Outdoor Scenes | Basic | null | openMUSE/muse-256 | 0 |
|
a boat | Vehicles | Basic | null | openMUSE/muse-256 | 0 |
|
a fox | Animals | Basic | null | openMUSE/muse-256 | 0 |
|
a red cube | Illustrations | Basic | null | openMUSE/muse-256 | 0 |
|
a panda | Animals | Basic | null | openMUSE/muse-256 | 0 |
|
a space elevator | Artifacts | Basic | GLIDE | openMUSE/muse-256 | 0 |
|
a city | Outdoor Scenes | Basic | null | openMUSE/muse-256 | 0 |
|
a fog | Outdoor Scenes | Basic | null | openMUSE/muse-256 | 0 |
|
a clock | Artifacts | Basic | null | openMUSE/muse-256 | 0 |
|
a phone | Artifacts | Basic | null | openMUSE/muse-256 | 0 |
|
food | Food & Beverage | Basic | null | openMUSE/muse-256 | 0 |
|
a store front | Outdoor Scenes | Basic | null | openMUSE/muse-256 | 0 |
|
an armchair | Artifacts | Basic | null | openMUSE/muse-256 | 0 |
|
a teapot | Artifacts | Basic | null | openMUSE/muse-256 | 0 |
|
an illustration of a teapot | Artifacts | Basic | DALL-E | openMUSE/muse-256 | 0 |
|
a tiger | Animals | Basic | null | openMUSE/muse-256 | 0 |
|
a bench | Artifacts | Basic | null | openMUSE/muse-256 | 0 |
|
an orange | Produce & Plants | Basic | null | openMUSE/muse-256 | 0 |
|
a laptop | Artifacts | Basic | null | openMUSE/muse-256 | 0 |
|
an owl | Animals | Basic | null | openMUSE/muse-256 | 0 |
|
a train | Vehicles | Basic | null | openMUSE/muse-256 | 0 |
|
a cow | Animals | Basic | null | openMUSE/muse-256 | 0 |
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YAML Metadata
Warning:
empty or missing yaml metadata in repo card
(https://huggingface.co/docs/hub/datasets-cards)
from PIL import Image
import torch
from muse import PipelineMuse, MaskGiTUViT
from datasets import Dataset, Features
from datasets import Image as ImageFeature
from datasets import Value, load_dataset
device = "cuda" if torch.cuda.is_available() else "cpu"
pipe = PipelineMuse.from_pretrained(
transformer_path="valhalla/research-run",
text_encoder_path="openMUSE/clip-vit-large-patch14-text-enc",
vae_path="openMUSE/vqgan-f16-8192-laion",
).to(device)
# pipe.transformer = MaskGiTUViT.from_pretrained("valhalla/research-run-finetuned-journeydb", revision="06bcd6ab6580a2ed3275ddfc17f463b8574457da", subfolder="ema_model").to(device)
pipe.transformer = MaskGiTUViT.from_pretrained("valhalla/muse-research-run", subfolder="ema_model").to(device)
pipe.tokenizer.pad_token_id = 49407
if device == "cuda":
pipe.transformer.enable_xformers_memory_efficient_attention()
pipe.text_encoder.to(torch.float16)
pipe.transformer.to(torch.float16)
import PIL
def main():
print("Loading dataset...")
parti_prompts = load_dataset("nateraw/parti-prompts", split="train")
print("Loading pipeline...")
seed = 0
device = "cuda"
torch.manual_seed(0)
ckpt_id = "openMUSE/muse-256"
scale = 10
print("Running inference...")
main_dict = {}
for i in range(len(parti_prompts)):
sample = parti_prompts[i]
prompt = sample["Prompt"]
image = pipe(
prompt,
timesteps=16,
negative_text=None,
guidance_scale=scale,
temperature=(2, 0),
orig_size=(256, 256),
crop_coords=(0, 0),
aesthetic_score=6,
use_fp16=device == "cuda",
transformer_seq_len=256,
use_tqdm=False,
)[0]
image = image.resize((256, 256), resample=PIL.Image.Resampling.LANCZOS)
img_path = f"/home/patrick/muse_images/muse_256_{i}.png"
image.save(img_path)
main_dict.update(
{
prompt: {
"img_path": img_path,
"Category": sample["Category"],
"Challenge": sample["Challenge"],
"Note": sample["Note"],
"model_name": ckpt_id,
"seed": seed,
}
}
)
def generation_fn():
for prompt in main_dict:
prompt_entry = main_dict[prompt]
yield {
"Prompt": prompt,
"Category": prompt_entry["Category"],
"Challenge": prompt_entry["Challenge"],
"Note": prompt_entry["Note"],
"images": {"path": prompt_entry["img_path"]},
"model_name": prompt_entry["model_name"],
"seed": prompt_entry["seed"],
}
print("Preparing HF dataset...")
ds = Dataset.from_generator(
generation_fn,
features=Features(
Prompt=Value("string"),
Category=Value("string"),
Challenge=Value("string"),
Note=Value("string"),
images=ImageFeature(),
model_name=Value("string"),
seed=Value("int64"),
),
)
ds_id = "diffusers-parti-prompts/muse256"
ds.push_to_hub(ds_id)
if __name__ == "__main__":
main()
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