Instructions to use tencent/HunyuanImage-2.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Inference
- Notebooks
- Google Colab
- Kaggle
Download vae/vae_refiner/config.json from tencent/HunyuanImage-2.1: direct link, hf CLI and curl.
- Browser
- Download file 514 Bytes
-
https://huggingface.co/tencent/HunyuanImage-2.1/resolve/main/vae/vae_refiner/config.json
- Command line
-
hf download hf://tencent/HunyuanImage-2.1/vae/vae_refiner/config.json
-
curl -L -o config.json https://huggingface.co/tencent/HunyuanImage-2.1/resolve/main/vae/vae_refiner/config.json
514 Bytes
| { | |
| "_class_name": "AutoencoderKLConv3D", | |
| "block_out_channels": [ | |
| 128, | |
| 256, | |
| 512, | |
| 1024, | |
| 1024 | |
| ], | |
| "in_channels": 3, | |
| "out_channels": 3, | |
| "latent_channels": 32, | |
| "layers_per_block": 2, | |
| "ffactor_spatial": 16, | |
| "ffactor_temporal": 4, | |
| "sample_size": 256, | |
| "sample_tsize": 64, | |
| "downsample_match_channel": true, | |
| "spatial_compression_ratio": 16, | |
| "time_compression_ratio": 4, | |
| "upsample_match_channel": true, | |
| "scaling_factor": 1.03682 | |
| } | |