Instructions to use ml-resources/MOSS-Image-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ml-resources/MOSS-Image-Base with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ml-resources/MOSS-Image-Base", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download transformer/config.json from ml-resources/MOSS-Image-Base: direct link, hf CLI and curl.
- Browser
- Download file 240 Bytes
-
https://huggingface.co/ml-resources/MOSS-Image-Base/resolve/main/transformer/config.json
- Command line
-
hf download hf://ml-resources/MOSS-Image-Base/transformer/config.json
-
curl -L -o config.json https://huggingface.co/ml-resources/MOSS-Image-Base/resolve/main/transformer/config.json
240 Bytes
| { | |
| "_class_name": "MOSSImageTransformer", | |
| "_diffusers_version": "0.38.0", | |
| "dim": 3072, | |
| "ffn_dim": 8192, | |
| "freq_dim": 256, | |
| "latent_channels": 128, | |
| "num_heads": 24, | |
| "num_layers": 42, | |
| "rope_base": 10000.0, | |
| "text_dim": 4096 | |
| } | |