Instructions to use REPA-E/e2e-qwenimage-vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use REPA-E/e2e-qwenimage-vae with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("REPA-E/e2e-qwenimage-vae", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
| { | |
| "_class_name": "AutoencoderKLQwenImage", | |
| "_diffusers_version": "0.35.0", | |
| "_name_or_path": "pretrained_models/qwenimage-vae-e2e-lr2e-5-400k", | |
| "attn_scales": [], | |
| "base_dim": 96, | |
| "dim_mult": [ | |
| 1, | |
| 2, | |
| 4, | |
| 4 | |
| ], | |
| "dropout": 0.0, | |
| "latents_mean": [ | |
| -0.04180605337023735, | |
| -0.015671083703637123, | |
| -0.005345471668988466, | |
| -0.01270077470690012, | |
| -0.04445185139775276, | |
| 0.03513055667281151, | |
| -0.03672828525304794, | |
| 0.023888064548373222, | |
| -0.03632868081331253, | |
| -0.004377194680273533, | |
| 0.03795469179749489, | |
| -0.001475810189731419, | |
| -0.08210355043411255, | |
| -0.10997337102890015, | |
| -0.04832911491394043, | |
| 0.007730678655207157 | |
| ], | |
| "latents_std": [ | |
| 2.334869623184204, | |
| 2.366467237472534, | |
| 2.3873367309570312, | |
| 2.3957691192626953, | |
| 2.377338409423828, | |
| 2.405400514602661, | |
| 2.390782356262207, | |
| 2.3725364208221436, | |
| 2.3622777462005615, | |
| 2.382412910461426, | |
| 2.4043378829956055, | |
| 2.36690354347229, | |
| 2.380032777786255, | |
| 2.3778722286224365, | |
| 2.388890027999878, | |
| 2.3639066219329834 | |
| ], | |
| "num_res_blocks": 2, | |
| "temperal_downsample": [ | |
| false, | |
| true, | |
| true | |
| ], | |
| "z_dim": 16 | |
| } | |