Instructions to use pinecoresystems/Ming-Image-0.1-Design 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 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", 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: direct link, hf CLI and curl.
- Browser
- Download file 12.2 MB
-
https://huggingface.co/pinecoresystems/Ming-Image-0.1-Design/resolve/main/mllm/tokenizer.json
- Command line
-
hf download hf://pinecoresystems/Ming-Image-0.1-Design/mllm/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/pinecoresystems/Ming-Image-0.1-Design/resolve/main/mllm/tokenizer.json
12.2 MB
- Xet hash:
- 5c86321b901616a898326699985d7ca2c2ddda9e9e5e21095def8219cf845323
- Size of remote file:
- 12.2 MB
- SHA256:
- e7ff01708d504f7bf4dbf7f5815adde57bab9a40e7f563ab6ad1acace4464917
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