Instructions to use codeShare/Flux2Klein_AIO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codeShare/Flux2Klein_AIO with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("codeShare/Flux2Klein_AIO", 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
- Local Apps
- Draw Things
- DiffusionBee
| { | |
| "_class_name": "Flux2Transformer2DModel", | |
| "_diffusers_version": "0.38.0.dev0", | |
| "_name_or_path": "/raid/yiyi/klein-4b-distilled-diffusers/transformer", | |
| "attention_head_dim": 128, | |
| "axes_dims_rope": [ | |
| 32, | |
| 32, | |
| 32, | |
| 32 | |
| ], | |
| "eps": 1e-06, | |
| "guidance_embeds": false, | |
| "in_channels": 128, | |
| "joint_attention_dim": 7680, | |
| "mlp_ratio": 3.0, | |
| "num_attention_heads": 24, | |
| "num_layers": 5, | |
| "num_single_layers": 20, | |
| "out_channels": null, | |
| "patch_size": 1, | |
| "rope_theta": 2000, | |
| "timestep_guidance_channels": 256 | |
| } | |