Text-to-Image
Diffusers
NeuronStableDiffusionXLPipeline
stable-diffusion
lora
template:sd-lora
Neuron
Inferentia
Instructions to use Shekswess/Canopus-Interior-Architecture-0.1-Neuron with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Shekswess/Canopus-Interior-Architecture-0.1-Neuron with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Shekswess/Canopus-Interior-Architecture-0.1-Neuron") prompt = "Interior room of the house with plants, a chair and candles, space to relax, soft lighting, pastel colors, style of ultrafine detail, high quality photo --ar 2:3 --v 5" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download model_index.json from Shekswess/Canopus-Interior-Architecture-0.1-Neuron: direct link, hf CLI and curl.
- Browser
- Download file 808 Bytes
-
https://huggingface.co/Shekswess/Canopus-Interior-Architecture-0.1-Neuron/resolve/main/model_index.json
- Command line
-
hf download hf://Shekswess/Canopus-Interior-Architecture-0.1-Neuron/model_index.json
-
curl -L -o model_index.json https://huggingface.co/Shekswess/Canopus-Interior-Architecture-0.1-Neuron/resolve/main/model_index.json
808 Bytes
| { | |
| "_class_name": "NeuronStableDiffusionXLPipeline", | |
| "_diffusers_version": "0.30.3", | |
| "_name_or_path": "stabilityai/stable-diffusion-xl-base-1.0", | |
| "feature_extractor": [ | |
| null, | |
| null | |
| ], | |
| "force_zeros_for_empty_prompt": true, | |
| "image_encoder": [ | |
| null, | |
| null | |
| ], | |
| "scheduler": [ | |
| "diffusers", | |
| "EulerDiscreteScheduler" | |
| ], | |
| "text_encoder": [ | |
| "optimum", | |
| "NeuronModelTextEncoder" | |
| ], | |
| "text_encoder_2": [ | |
| "optimum", | |
| "NeuronModelTextEncoder" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "CLIPTokenizer" | |
| ], | |
| "tokenizer_2": [ | |
| "transformers", | |
| "CLIPTokenizer" | |
| ], | |
| "unet": [ | |
| "optimum", | |
| "NeuronModelUnet" | |
| ], | |
| "vae_decoder": [ | |
| "optimum", | |
| "NeuronModelVaeDecoder" | |
| ], | |
| "vae_encoder": [ | |
| "optimum", | |
| "NeuronModelVaeEncoder" | |
| ] | |
| } | |