Instructions to use zeyuren2002/EvalMDE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zeyuren2002/EvalMDE with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("zeyuren2002/EvalMDE", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
File size: 693 Bytes
40a3ea8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | import logging
import sys
def setup_logging(args=None, log_level=None, reset=False):
if logging.root.handlers:
if reset:
for handler in logging.root.handlers[:]:
logging.root.removeHandler(handler)
else:
return
if log_level is None and args is not None:
log_level = getattr(args, "console_log_level", None)
if log_level is None:
log_level = "INFO"
log_level = getattr(logging, str(log_level).upper())
handler = logging.StreamHandler(sys.stdout)
handler.setFormatter(logging.Formatter("%(message)s"))
logging.root.setLevel(log_level)
logging.root.addHandler(handler)
setup_logging()
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