Instructions to use mingyi456/ERNIE-Image-DF11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mingyi456/ERNIE-Image-DF11 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mingyi456/ERNIE-Image-DF11", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Diffusion Single File
How to use mingyi456/ERNIE-Image-DF11 with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| { | |
| "dfloat11_config": { | |
| "version": "0.5.0", | |
| "threads_per_block": [ | |
| 512 | |
| ], | |
| "bytes_per_thread": 8, | |
| "pattern_dict": { | |
| "time_embedding": [ | |
| "linear_1", | |
| "linear_2" | |
| ], | |
| "adaLN_modulation.1": [], | |
| "layers\\.\\d+": [ | |
| "self_attention.to_q", | |
| "self_attention.to_k", | |
| "self_attention.to_v", | |
| "self_attention.to_out.0", | |
| "mlp.gate_proj", | |
| "mlp.up_proj", | |
| "mlp.linear_fc2" | |
| ], | |
| "final_norm.linear": [] | |
| } | |
| } | |
| } |