Instructions to use pinecoresystems/Ming-Image-0.1-Design-Layer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use pinecoresystems/Ming-Image-0.1-Design-Layer with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("pinecoresystems/Ming-Image-0.1-Design-Layer", 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 mllm/tokenizer.json from pinecoresystems/Ming-Image-0.1-Design-Layer: direct link, hf CLI and curl.
- Browser
- Download file 12.2 MB
-
https://huggingface.co/pinecoresystems/Ming-Image-0.1-Design-Layer/resolve/main/mllm/tokenizer.json
- Command line
-
hf download hf://pinecoresystems/Ming-Image-0.1-Design-Layer/mllm/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/pinecoresystems/Ming-Image-0.1-Design-Layer/resolve/main/mllm/tokenizer.json
12.2 MB
- Xet hash:
- 6e097afc6fa82484259c7ca66534d1c1d77eb8f63f210681274e73ed026a1d60
- Size of remote file:
- 12.2 MB
- SHA256:
- e4f5fe09e7484071da5fa93cfb82f7db15c0ebf9b6ee9821599c5a997563ee96
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