Image-to-Image
Transformers
Safetensors
English
ditfuse
image-fusion
infrared-visible-fusion
multi-focus-fusion
multi-exposure-fusion
diffusion
transformer
multimodal
text-guided
Instructions to use lijiayangCS/DiTFuse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lijiayangCS/DiTFuse with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-to-image", model="lijiayangCS/DiTFuse")# Load model directly from transformers import DiTFuse model = DiTFuse.from_pretrained("lijiayangCS/DiTFuse", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "alpha_pattern": {}, | |
| "auto_mapping": { | |
| "base_model_class": "OmniGen", | |
| "parent_library": "OmniGen.model" | |
| }, | |
| "base_model_name_or_path": null, | |
| "bias": "none", | |
| "corda_config": null, | |
| "eva_config": null, | |
| "exclude_modules": null, | |
| "fan_in_fan_out": false, | |
| "inference_mode": true, | |
| "init_lora_weights": "gaussian", | |
| "layer_replication": null, | |
| "layers_pattern": null, | |
| "layers_to_transform": null, | |
| "loftq_config": {}, | |
| "lora_alpha": 64, | |
| "lora_bias": false, | |
| "lora_dropout": 0.0, | |
| "megatron_config": null, | |
| "megatron_core": "megatron.core", | |
| "modules_to_save": null, | |
| "peft_type": "LORA", | |
| "r": 64, | |
| "rank_pattern": {}, | |
| "revision": null, | |
| "target_modules": [ | |
| "o_proj", | |
| "qkv_proj" | |
| ], | |
| "task_type": null, | |
| "trainable_token_indices": null, | |
| "use_dora": false, | |
| "use_rslora": false | |
| } |