woctezuma / stable-diffusion-colab Goto Github PK
View Code? Open in Web Editor NEWColab notebook for Stable Diffusion Hyper-SDXL.
Home Page: https://github.com/Stability-AI/generative-models
License: MIT License
Colab notebook for Stable Diffusion Hyper-SDXL.
Home Page: https://github.com/Stability-AI/generative-models
License: MIT License
Switch model weights to stabilityai/stable-diffusion-2-1 (weights).
Thanks for making this.
I have two issue:
"WARNING:root:A matching Triton is not available, some optimizations will not be enabled.
Error caught was: No module named 'triton'"
But I was able to generate images without any issue.
from numba import cuda
import torch
device = cuda.get_current_device()
device.reset()
and it did empty the gpu memory but somehow detach the cuda device from the notebook!
CUDA error: invalid argument
CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
How can we load lora model(just a single file as .safetensors)?
Getting this error on the pipe.enable_xformers_memory_efficient_attention() step:
RuntimeError Traceback (most recent call last)
[<ipython-input-5-4f0f5a2b85ee>](https://localhost:8080/#) in <module>
12 )
13 pipe = pipe.to(device)
---> 14 pipe.enable_xformers_memory_efficient_attention()
15
16 if model_id.endswith('-base'):
15 frames
[/usr/local/lib/python3.8/dist-packages/xformers/ops.py](https://localhost:8080/#) in no_such_operator(*args, **kwargs)
44 def _get_xformers_operator(name: str):
45 def no_such_operator(*args, **kwargs):
---> 46 raise RuntimeError(
47 f"No such operator xformers::{name} - did you forget to build xformers with `python setup.py develop`?"
48 )
RuntimeError: No such operator xformers::efficient_attention_forward_cutlass - did you forget to build xformers with `python setup.py develop`?
Any advice? Thanks
To Whom It May Concern:
I have published a stand-alone textual inversion implementation for Stable Diffusion XL - NO additional frameworks, just a Jupyter notebook, works on your local 24GB GPU e.g. RTX 3090:
https://github.com/oss-roettger/XL-Textual-Inversion
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