Any-to-Any
Transformers
Diffusers
Safetensors
text-to-image
image-editing
image-understanding
vision-language
multimodal
autoregressive
unified-model
Instructions to use Skywork/UniPic2-SD3.5M-Kontext-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Skywork/UniPic2-SD3.5M-Kontext-2B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Skywork/UniPic2-SD3.5M-Kontext-2B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download scheduler/scheduler_config.json from Skywork/UniPic2-SD3.5M-Kontext-2B: direct link, hf CLI and curl.
- Browser
- Download file 487 Bytes
-
https://huggingface.co/Skywork/UniPic2-SD3.5M-Kontext-2B/resolve/main/scheduler/scheduler_config.json
- Command line
-
hf download hf://Skywork/UniPic2-SD3.5M-Kontext-2B/scheduler/scheduler_config.json
-
curl -L -o scheduler_config.json https://huggingface.co/Skywork/UniPic2-SD3.5M-Kontext-2B/resolve/main/scheduler/scheduler_config.json
487 Bytes
| { | |
| "_class_name": "FlowMatchEulerDiscreteScheduler", | |
| "_diffusers_version": "0.35.0.dev0", | |
| "base_image_seq_len": 256, | |
| "base_shift": 0.5, | |
| "invert_sigmas": false, | |
| "max_image_seq_len": 4096, | |
| "max_shift": 1.15, | |
| "num_train_timesteps": 1000, | |
| "shift": 3.0, | |
| "shift_terminal": null, | |
| "stochastic_sampling": false, | |
| "time_shift_type": "exponential", | |
| "use_beta_sigmas": false, | |
| "use_dynamic_shifting": false, | |
| "use_exponential_sigmas": false, | |
| "use_karras_sigmas": false | |
| } | |