Instructions to use sayakpaul/show-1-base-with-code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sayakpaul/show-1-base-with-code with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("sayakpaul/show-1-base-with-code", 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
| { | |
| "_class_name": ["pipeline_t2v_base_pixel", "TextToVideoIFPipeline"], | |
| "_diffusers_version": "0.22.0.dev0", | |
| "feature_extractor": [ | |
| "transformers", | |
| "CLIPFeatureExtractor" | |
| ], | |
| "scheduler": [ | |
| "diffusers", | |
| "DPMSolverMultistepScheduler" | |
| ], | |
| "text_encoder": [ | |
| "transformers", | |
| "T5EncoderModel" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "T5Tokenizer" | |
| ], | |
| "unet": [ | |
| "showone_unet_3d_condition", | |
| "ShowOneUNet3DConditionModel" | |
| ] | |
| } | |