Instructions to use g-ronimo/hana-alpha41_e34 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use g-ronimo/hana-alpha41_e34 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("g-ronimo/hana-alpha41_e34", 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": "SanaTransformer2DModel", | |
| "_diffusers_version": "0.33.0.dev0", | |
| "_name_or_path": "./cp-e34", | |
| "attention_bias": false, | |
| "attention_head_dim": 32, | |
| "caption_channels": 960, | |
| "cross_attention_dim": 1152, | |
| "cross_attention_head_dim": 32, | |
| "dropout": 0.0, | |
| "in_channels": 32, | |
| "interpolation_scale": null, | |
| "mlp_ratio": 2.5, | |
| "norm_elementwise_affine": false, | |
| "norm_eps": 1e-06, | |
| "num_attention_heads": 36, | |
| "num_cross_attention_heads": 36, | |
| "num_layers": 28, | |
| "out_channels": 32, | |
| "patch_size": 1, | |
| "sample_size": 32 | |
| } | |