Instructions to use Erland/tiny-wan2.1-t2v-debug with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Erland/tiny-wan2.1-t2v-debug with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Erland/tiny-wan2.1-t2v-debug", 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
| { | |
| "_class_name": "WanTransformer3DModel", | |
| "_diffusers_version": "0.37.1", | |
| "added_kv_proj_dim": null, | |
| "attention_head_dim": 16, | |
| "cross_attn_norm": true, | |
| "eps": 1e-06, | |
| "ffn_dim": 64, | |
| "freq_dim": 32, | |
| "image_dim": null, | |
| "in_channels": 4, | |
| "num_attention_heads": 2, | |
| "num_layers": 1, | |
| "out_channels": 4, | |
| "patch_size": [ | |
| 1, | |
| 2, | |
| 2 | |
| ], | |
| "pos_embed_seq_len": null, | |
| "qk_norm": "rms_norm_across_heads", | |
| "rope_max_seq_len": 64, | |
| "text_dim": 32 | |
| } | |