| | |
| | |
| | from diffusers import DiffusionPipeline |
| | import torch |
| | import time |
| | import os |
| | from pathlib import Path |
| | from huggingface_hub import HfApi |
| |
|
| | api = HfApi() |
| | start_time = time.time() |
| |
|
| | pipe = DiffusionPipeline.from_pretrained("/home/patrick/if", torch_dtype=torch.float16, variant="fp16", use_safetensors=True) |
| | pipe.enable_model_cpu_offload() |
| |
|
| | generator = torch.Generator("cuda").manual_seed(0) |
| | prompt = 'a photo of a kangaroo wearing an orange hoodie and blue sunglasses standing in front of the eiffel tower holding a sign that says "very deep learning"' |
| |
|
| | image = pipe(prompt, generator=generator).images[0] |
| |
|
| | path = os.path.join(Path.home(), "images", "if.png") |
| | image.save(path) |
| |
|
| | api.upload_file( |
| | path_or_fileobj=path, |
| | path_in_repo=path.split("/")[-1], |
| | repo_id="patrickvonplaten/images", |
| | repo_type="dataset", |
| | ) |
| | print(f"https://huggingface.co/datasets/patrickvonplaten/images/blob/main/if.png") |
| |
|
