Instructions to use Sen-sou/Anima-LLLite-Regional-Controlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Sen-sou/Anima-LLLite-Regional-Controlnet with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| base_model: | |
| - circlestone-labs/Anima | |
| tags: | |
| - peft | |
| - lora | |
| - adapter | |
| # Experimental Anima LLLite Regional Controlnet | |
| Apply Anima ControlNet-LLLite parameters: | |
|  | |
| Control image example: (Use basic colors as region) | |
|  | |
| Prompt: (kinda works) | |
| base prompt | |
| region color: region prompt | |
| ## Training Parameters: | |
| caption_extension: .txt | |
| shuffle_caption: false | |
| resolution: 1024 | |
| batch_size: 1 | |
| enable_bucket: true | |
| bucket_no_upscale: true | |
| bucket_reso_steps: 16 | |
| min_bucket_reso: 64 | |
| max_bucket_reso: 1536 | |
| num_repeats: 2 | |
| 580 image/control/caption pairs | |
| 580 * 2 repeats = 1160 steps per epoch | |
| 8 epochs = 9280 total steps | |
| learning_rate: 3e-4 | |
| max_train_epochs: 8 | |
| seed: 42 | |
| optimizer: AdamW8bit | |
| lr_scheduler: constant | |
| mixed_precision: bf16 | |
| save_precision: bf16 | |
| save_model_as: safetensors | |
| save_every_n_epochs: 1 | |
| gradient_checkpointing: enabled | |
| cache_latents_to_disk: enabled | |
| cache_text_encoder_outputs_to_disk: enabled | |
| vae_chunk_size: 64 | |
| vae_disable_cache: enabled | |
| timestep_sampling: shift | |
| discrete_flow_shift: 3.0 | |
| attn_mode: torch | |
| cond_emb_dim: 32 | |
| lllite_cond_dim: 64 | |
| lllite_mlp_dim: 64 | |
| lllite_target_layers: self_attn_qkv | |
| lllite_cond_resblocks: 4 | |
| lllite_use_aspp: enabled | |
| caption_dropout_rate: 0.15 | |