Instructions to use VAST-AI/TripoSG-scribble with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use VAST-AI/TripoSG-scribble with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("VAST-AI/TripoSG-scribble", torch_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: 674 Bytes
51ade01 | 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 26 27 28 29 30 31 32 33 | {
"_class_name": "TripoSGScribblePipeline",
"_diffusers_version": "0.33.1",
"feature_extractor_dinov2": [
"transformers",
"BitImageProcessor"
],
"image_encoder_dinov2": [
"transformers",
"Dinov2Model"
],
"scheduler": [
"triposg.schedulers.scheduling_rectified_flow",
"RectifiedFlowScheduler"
],
"text_encoder": [
"transformers",
"CLIPTextModelWithProjection"
],
"tokenizer": [
"transformers",
"CLIPTokenizer"
],
"transformer": [
"triposg.models.transformers.triposg_transformer",
"TripoSGDiTModel"
],
"vae": [
"triposg.models.autoencoders.autoencoder_kl_triposg",
"TripoSGVAEModel"
]
}
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