Instructions to use Runware/pony-v7-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Runware/pony-v7-base with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Runware/pony-v7-base", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| # Pony V7 LoRA Training | |
| ## Training Guide | |
| We recommend using SimpleTuner for LoRA training following [this guide](https://github.com/bghira/SimpleTuner/blob/main/documentation/quickstart/AURAFLOW.md). | |
| ## ComfyUI LoRA Workflow | |
| A [LoRA workflow example](../workflows/pony-v7-lora.png) is available showing how to load and use LoRAs with Pony V7. Simply drag and drop the workflow image into your ComfyUI canvas to load it. | |
| ## LoRA Conversion Script | |
| ### [convert_simpletuner_lora.py](convert_simpletuner_lora.py) | |
| A utility script to convert SimpleTuner LoRA weights to diffusers-compatible format for AuraFlow models. | |
| **Usage:** | |
| ```bash | |
| python convert_simpletuner_lora.py <input_lora.safetensors> <output_lora.safetensors> | |
| ``` | |
| This script ensures your LoRAs trained with SimpleTuner can be loaded directly with diffusers' `load_lora_weights()` method or inside of ComfyUI's LoRA nodes. | |