* [Community Pipeline] Add Marigold Monocular Depth Estimation
- add single-file pipeline
- update README
* fix format - add one blank line
* format script with ruff
* use direct image link in example code
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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* LLMGroundedDiffusionPipeline: inherit from DiffusionPipeline and fix peft
* Use main in the revision in the examples
* Add "Copied from" statements in comments
* Fix formatting with ruff
* make `requires_safety_checker` a kwarg instead of a positional argument as it's more future-proof
* apply `make style` formatting edits
* add image_encoder to arguments and pass to super constructor
* bug in MultiAdapter for Inpainting
* adapter_input is a list for MultiAdapter
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Co-authored-by: andres <andres@hax.ai>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* fix an issue that ipex occupy too much memory, it will not impact performance
* make style
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Co-authored-by: root <jun.chen@intel.com>
Co-authored-by: Meng Guoqing <guoqing.meng@intel.com>
* Fix the pipeline name in the examples for LMD+ pipeline
* Add LMD+ colab link
* Apply code formatting
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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Add a new community pipeline
examples/community/latent_consistency_img2img.py
which can be called like this
import torch
from diffusers import DiffusionPipeline
pipe = DiffusionPipeline.from_pretrained(
"SimianLuo/LCM_Dreamshaper_v7", custom_pipeline="latent_consistency_txt2img", custom_revision="main")
# To save GPU memory, torch.float16 can be used, but it may compromise image quality.
pipe.to(torch_device="cuda", torch_dtype=torch.float32)
img2img=LatentConsistencyModelPipeline_img2img(
vae=pipe.vae,
text_encoder=pipe.text_encoder,
tokenizer=pipe.tokenizer,
unet=pipe.unet,
#scheduler=pipe.scheduler,
scheduler=None,
safety_checker=None,
feature_extractor=pipe.feature_extractor,
requires_safety_checker=False,
)
img = Image.open("thisismyimage.png")
result = img2img(prompt,img,strength,num_inference_steps=4)
* Apply suggestions from code review
Fix name formatting for scheduler
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* update readme (and run formatter on latent_consistency_img2img.py)
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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* SDXL microconditioning documentation should indicate the correct default order of parameters, so that developers know
* SDXL microconditioning documentation should indicate the correct default order of parameters, so that developers know
* empty
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Co-authored-by: bghira <bghira@users.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Fixed `get_word_inds` mistake/typo in P2P community pipeline
The function `get_word_inds` was taking a string of text and either a word (str) or a word index (int) and returned the indices of token(s) the word would be encoded to.
However, there was a typo, in which in the second `if` branch the word was checked to be a `str` **again**, not `int`, which resulted in an [example code from the docs](https://github.com/huggingface/diffusers/tree/main/examples/community#prompt2prompt-pipeline) to result in an error
