Any-to-Any
Transformers
Diffusers
Safetensors
English
llada2_moe
feature-extraction
multimodal
image-generation
image-understanding
image-editing
diffusion
Mixture of Experts
text-to-image
fp8
quantized
custom_code
Instructions to use inclusionAI/LLaDA2.0-Uni-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use inclusionAI/LLaDA2.0-Uni-FP8 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("inclusionAI/LLaDA2.0-Uni-FP8", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download decoder/config.json from inclusionAI/LLaDA2.0-Uni-FP8: direct link, hf CLI and curl.
- Browser
- Download file 500 Bytes
-
https://huggingface.co/inclusionAI/LLaDA2.0-Uni-FP8/resolve/main/decoder/config.json
- Command line
-
hf download hf://inclusionAI/LLaDA2.0-Uni-FP8/decoder/config.json
-
curl -L -o config.json https://huggingface.co/inclusionAI/LLaDA2.0-Uni-FP8/resolve/main/decoder/config.json
500 Bytes
| { | |
| "_class_name": "ZImageTransformer2DModel", | |
| "_diffusers_version": "0.37.0.dev0", | |
| "all_f_patch_size": [ | |
| 1 | |
| ], | |
| "all_patch_size": [ | |
| 2 | |
| ], | |
| "axes_dims": [ | |
| 32, | |
| 48, | |
| 48 | |
| ], | |
| "axes_lens": [ | |
| 1536, | |
| 512, | |
| 512 | |
| ], | |
| "cap_feat_dim": 4096, | |
| "dim": 3840, | |
| "in_channels": 16, | |
| "n_heads": 30, | |
| "n_kv_heads": 30, | |
| "n_layers": 30, | |
| "n_refiner_layers": 2, | |
| "norm_eps": 1e-05, | |
| "qk_norm": true, | |
| "rope_theta": 256.0, | |
| "siglip_feat_dim": null, | |
| "t_scale": 1000.0 | |
| } | |