Instructions to use aztro/IATNAT-LORA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aztro/IATNAT-LORA with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
IATNAT LoRA
LoRA entrenado sobre LTX-2.5 (Lightricks) con ai-toolkit
para generar video a partir de texto con el sujeto iatnat.
Trigger word
Usa iatnat al inicio del prompt. Ejemplo:
iatnat, a woman with long black hair sitting on a brown recliner, looking at the camera, soft indoor lighting
Sin la trigger word, el LoRA apenas tendrá efecto sobre el sujeto.
Detalles de entrenamiento
| Parámetro | Valor |
|---|---|
| Modelo base | Lightricks/LTX-2.5 |
| Arquitectura | LTX-2.5 |
| Tipo de red | LoRA |
| Rank linear / alpha | 32 / 32 |
| Rank conv / alpha | 16 / 16 |
| Steps | 2000 |
| Batch size | 1 |
| Gradient accumulation | 1 |
| Learning rate | 1e-4 |
| Optimizer | adamw8bit |
| Scheduler de ruido | flowmatch |
| Timestep type | weighted |
| Precisión | bf16 |
| Quantization | convrot8 (transformer + text encoder) |
| Resoluciones de entrenamiento | 512 / 768 / 1024 |
| num_frames (train) | 1 (modo imagen) |
| num_repeats | 5 |
| Caption dropout | 0.05 |
| Save every | 250 steps (max 4 checkpoints) |
| Formato de guardado | diffusers |
| Trigger word | iatnat |
Formato del archivo
El repo contiene el LoRA en formato diffusers (carpetas transformer/, model_index.json, etc.).
Si tu pipeline (ComfyUI, A1111, Forge, diffusers) espera un .safetensors plano, convierte el checkpoint o vuelve a exportarlo desde ai-toolkit con:
save:
save_format: safetensors
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Model tree for aztro/IATNAT-LORA
Base model
Lightricks/LTX-2.5