Instructions to use CodeGoat24/Wan2.1-T2V-14B-UnifiedReward-Flex-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CodeGoat24/Wan2.1-T2V-14B-UnifiedReward-Flex-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CodeGoat24/Wan2.1-T2V-14B-UnifiedReward-Flex-lora", 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
| { | |
| "step": 151, | |
| "lora_params": { | |
| "lora_rank": 64, | |
| "lora_alpha": 128, | |
| "target_modules": [ | |
| "add_k_proj", | |
| "add_q_proj", | |
| "add_v_proj", | |
| "to_add_out", | |
| "to_k", | |
| "to_out.0", | |
| "to_q", | |
| "to_v" | |
| ] | |
| } | |
| } |