Instructions to use metercai/SimpleSDXL2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use metercai/SimpleSDXL2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("metercai/SimpleSDXL2", 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
Download SimpleModels/llms/MiniCPMv2_6-prompt-generator/preprocessor_config.json from metercai/SimpleSDXL2: direct link, hf CLI and curl.
- Browser
- Download file 714 Bytes
-
https://huggingface.co/metercai/SimpleSDXL2/resolve/main/SimpleModels/llms/MiniCPMv2_6-prompt-generator/preprocessor_config.json
- Command line
-
hf download hf://metercai/SimpleSDXL2/SimpleModels/llms/MiniCPMv2_6-prompt-generator/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/metercai/SimpleSDXL2/resolve/main/SimpleModels/llms/MiniCPMv2_6-prompt-generator/preprocessor_config.json
714 Bytes
| { | |
| "image_processor_type": "MiniCPMVImageProcessor", | |
| "auto_map": { | |
| "AutoProcessor": "processing_minicpmv.MiniCPMVProcessor", | |
| "AutoImageProcessor": "image_processing_minicpmv.MiniCPMVImageProcessor" | |
| }, | |
| "processor_class": "MiniCPMVProcessor", | |
| "max_slice_nums": 9, | |
| "scale_resolution": 448, | |
| "patch_size": 14, | |
| "use_image_id": true, | |
| "image_feature_size": 64, | |
| "im_start": "<image>", | |
| "im_end": "</image>", | |
| "slice_start": "<slice>", | |
| "slice_end": "</slice>", | |
| "unk": "<unk>", | |
| "im_id_start": "<image_id>", | |
| "im_id_end": "</image_id>", | |
| "slice_mode": true, | |
| "norm_mean": [0.5, 0.5, 0.5], | |
| "norm_std": [0.5, 0.5, 0.5], | |
| "version": 2.6 | |
| } |