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
File size: 473 Bytes
c542df0 34109c6 c542df0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | {
"_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"
]
}
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